Identification of nine new susceptibility loci for endometrial cancer

Causality of genetically predicted solid cancers on risk of sepsis: insights from Mendelian randomization

OBJECTIVE

Some studies have found that solid cancer and sepsis are linked. The primary objective of this study is to explore this connection further, investigating the causal effect of solid cancer on sepsis by applying Mendelian randomization (MR).

METHODS

Using genome-wide association study (GWAS) data from the Medical Research Council-Integrative Epidemiology Unit database, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis to test the causal association between solid cancers (10 GWAS, 1,345,730 samples) and sepsis (2 GWAS, 1,288,566 samples) in European ancestry. In the context of multivariable MR analysis, lifestyle risk factors such as body mass index (BMI) were incorporated, with relevant clinical interventions taken into account.

RESULTS

The two-sample MR analysis suggested a causal relationship between renal cancer and sepsis (OR = 1.051, 95% CI = 1.019-1.085, PIVW = 1.800E-03). Renal cancer (OR = 1.064, 95% CI = 1.011-1.120, PIVW = 1.60E-02), BMI (OR = 1.315, 95% CI = 1.176-1.471, PIVW = 1.25E-06), and smoking (OR = 1.139, 95% CI = 1.009-1.286, PIVW = 3.65E-02) showed a significant association with sepsis in our lifestyle multivariable MR analysis. Reverse MR analysis indicates that sepsis may prevent renal cancer. (OR = 0.924, 95% CI = 0.865 -0.988, PIVW = 2.060E-02).

CONCLUSIONS

Our findings suggest renal cancer is correlated with the occurrence of sepsis. This association is partially influenced by BMI and smoking. Unexpectedly, sepsis may act as a protective effect against renal cancer.

Ambient air pollution and the risk of cancer: Evidence from global cohort studies and epigenetic-related causal inference

The correlation between air pollution and cancer incidence has been a longstanding concern, understanding the need to elucidate the specifics of this relationship. Thus, this study aimed to assess the association between exposure to air pollution and cancer incidence, and to identify the possible biological links between the two. We examined global cohort studies investigating the association between air pollution and cancer and performed a univariate Mendelian randomization (MR) analysis. Our analysis revealed that the presence of particulate matter (PM)2.5, PM10, NO2, and NOx substantially impacted the risk of developing cancer. MR analysis identified 130 CpGs sites associated with three ambient air pollutants that have significant casual effects on the risk of 14 cancer sites (false discovery rate<0.05). Gene annotation was conducted using g-Profiler by screening for single nucleotide polymorphisms significantly associated with outcome, followed by analysis of the gene interaction network using GeneMANIA, and visualization using igraph. In conclusion, this study demonstrates that air pollution has a significant impact on cancer incidence, provides strong evidence for an epigenetic causal link between the two, and provides new insights into the molecular mechanisms by which air pollution affects cancer development.

Genetic insights support PARP1 as a mediator in the protective association of ATP-citrate lyase inhibitors with melanoma

ATP-citrate lyase (ACLY) inhibitors emerge as a promising anti-cancer strategy, yet their causal effects across various cancer types remain unclear. Here, we employ a drug-target Mendelian randomization (MR) approach using four cis-expression quantitative trait loci for blood ACLY gene expression as genetic instruments to mimic ACLY inhibition. We utilize genetic data from the eQTLGen consortium (N = 31,684) for ACLY expression, the deCODE study (N = 35,559) for plasma proteome, and large-scale cancer genome-wide association studies consortia (N from 49,708 to 417,127) to investigate the association of genetically mimicked ACLY inhibitors with 17 cancers and identify potential mediating proteins. Genetically proxied ACLY inhibition is strongly associated with reduced melanoma risk (odds ratio [95% confidence interval (CI)]: 0.85 [0.78, 0.92]) in a combined analysis of two independent outcome datasets. Proteome-wide MR screening 1517 plasma proteins identifies 3 proteins associated with melanoma, with Poly [ADP-ribose] polymerase 1 (PARP1) showing strong colocalization support. Mediation analysis further suggests PARP1 as a mediator in the protective effect of ACLY inhibition on melanoma (mediated proportion [95% CI]: 51.52% [5.45%, 97.58%]). Follow-up and validation analyses support the robustness of these results. This study illuminates the therapeutic potential of ACLY inhibition in melanoma, with PARP1 implicated as a potential mediator, offering avenues for targeted interventions.

Mapping Inherited Genetic Variation with Opposite Effects on Autoimmune Disease and Four Cancer Types Identifies Candidate Drug Targets Associated with the Anti-Tumor Immune Response

Background: Germline alleles near genes encoding certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer, but in opposite ways. This motivates a systematic search for additional germline alleles with this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetics. Methods: Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. Results: Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with p < 5 × 10-8 associated with at least one of the cancer types at p < 10-3 and one of the autoimmune/autoinflammatory diseases at p < 10-3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping led variants to nearest genes as putative functional targets and focusing on immune-related genes implicated 32 genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) was each strongly correlated (Spearman's ρ > 0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via the expression of quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable. Conclusions: We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3 and LAT as possible targets for cancer immunotherapy.

Dissecting the genetic determinants and biological associations between body mass index and female reproductive disorders based on genome-wide association study

BACKGROUND

While the phenotypic link between body mass index (BMI) and some female reproductive disorders is well established, the genetic architecture and causal relationships have not been systematically studied. We aimed to create an atlas of the shared genetic associations of BMI and 16 female reproductive disorders and to identify their common risk loci, biological pathways, and potential mechanisms.

METHODS

We assessed the genetic correlations between BMI and 16 reproductive disorders using summary data from large-scale genome-wide association studies. Cross-trait pleiotropic analysis identified shared loci and genes, while functional annotation and tissue-specific analysis revealed relevant biological pathways and tissues. Multi-trait colocalization analysis examined the role of hormones and metabolites in these traits. Additionally, bidirectional Mendelian randomization (MR) analysis was employed to assess causal relationships between BMI and reproductive outcomes. We also conducted summary data-based MR (SMR) analysis to identify potential drug targets.

RESULTS

Our results revealed a significant genetic correlation between BMI and eight female reproductive diseases. Furthermore, we identified 50 shared pleiotropic loci between BMI and these traits, with 21 of them showing significant colocalization, suggesting a complex shared genetic architecture across the genome. In addition, the top biological pathways and tissues enriched with these pleiotropic loci were associated with RNA metabolism, macromolecule biosynthesis, type B pancreatic cell apoptosis, various brain regions, and the pituitary. Moreover, multi-trait colocalization indicated that insulin, lipid metabolites, glucose, glycine, and glutamine mediate shared mechanisms between BMI, gestational diabetes mellitus (GDM), and endometrial cancer. MR analysis suggested BMI may cause several reproductive diseases, with only GDM affecting BMI reversely. Finally, SMR analysis revealed EIF2S2P3 and MCM6, which may have a causative effect on both BMI & GDM and BMI & gestational hypertension.

CONCLUSION

Our results suggest a significant genetic link between BMI and eight female reproductive diseases, highlighting a shared and causal genetic basis. Reducing BMI in women may serve as an effective strategy to lower the risk of female reproductive disorders. The identified pleiotropic loci, genes, and shared pathways could provide new therapeutic targets for both obesity and reproductive diseases, along with their comorbidities.

CLINICAL TRIAL NUMBER

Not applicable.

Research trends and hotspots of single nucleotide polymorphisms in endometrial cancer: a bibliometric analysis

BACKGROUND

Endometrial cancer (EC) is a common gynecological malignancy with increasing incidence, especially in developed nations. Understanding genetic variations, particularly single nucleotide polymorphisms (SNPs), is crucial for uncovering the disease's pathogenesis, progression, and treatment responses. This study explores the global research landscape of SNPs in EC, focusing on field evolution, key contributors, and emerging trends.

METHODS

A systematic search of the Web of Science Core Collection (WoSCC) retrieved 838 publications on SNPs in EC from 1991 to 2024. Bibliometric indicators, including publication volume, citation counts, and keyword occurrences, were analyzed using VOSviewer, CiteSpace, and the R package "bibliometrix" for visual mapping and trend analysis.

RESULTS

The United States (230 publications) and China (182 publications) were leaders in research output. Harvard University and the National Cancer Institute were prominent contributors. Key themes included "microsatellite instability" (a hallmark of DNA mismatch repair deficiency) and "genome-wide association studies" (GWAS), identifying susceptibility loci like HNF1B and CYP19A1. Recent trends, such as "Mendelian randomization," have enhanced causal inference in risk factor studies. SNP research has advanced risk prediction models and personalized therapeutic strategies, such as hormone therapy tailored to genetic profiles.

CONCLUSION

SNP research has deepened our understanding of EC's genetic basis, with a growing emphasis on Mendelian randomization and GWAS. These advancements have refined risk prediction and opened new avenues for personalized medicine. Integrating SNP data with environmental and hormonal factors remains crucial for advancing prevention, diagnosis, and treatment strategies in EC.

Endometrial tumorigenesis involves epigenetic plasticity demarcating non-coding somatic mutations and 3D-genome alterations

BACKGROUND

The incidence and mortality of endometrial cancer (EC) is on the rise. Eighty-five percent of ECs depend on estrogen receptor alpha (ERα) for proliferation, but little is known about its transcriptional regulation in these tumors.

RESULTS

We generate epigenomics, transcriptomics, and Hi-C datastreams in healthy and tumor endometrial tissues, identifying robust ERα reprogramming and profound alterations in 3D genome organization that lead to a gain of tumor-specific enhancer activity during EC development. Integration with endometrial cancer risk single-nucleotide polymorphisms and whole-genome sequencing data from primary tumors and metastatic samples reveals a striking enrichment of risk variants and non-coding somatic mutations at tumor-enriched ERα sites. Through machine learning-based predictions and interaction proteomics analyses, we identify an enhancer mutation which alters 3D genome conformation, impairing recruitment of the transcriptional repressor EHMT2/G9a/KMT1C, thereby alleviating transcriptional repression of ESR1 in EC.

CONCLUSIONS

In summary, we identify a complex genomic-epigenomic interplay in EC development and progression, altering 3D genome organization to enhance expression of the critical driver ERα.

Causal Associations of Obstructive Sleep Apnea With Cancer Risk: A Mendelian Randomization Study

BACKGROUND

Observational studies have associated obstructive sleep apnea (OSA) with a higher risk of various cancers; however, causal relationships have not yet been definitively established.

METHODS

Our study evaluated the causal impact of OSA on the risk of developing 22 different types of cancer using univariable and multivariable Mendelian randomization (MR). OSA-associated genetic instruments were obtained from the FinnGen study, which incorporates 38,998 OSA individuals and 336,659 non-OSA individuals from European descent. Summary-level data for 22 site-specific cancers were estimated from large genetic consortia and UK Biobank. We used inverse-variance weighting (IVW) as the primary analysis, along with several sensitivity analyses.

RESULTS

Univariable MR analyses indicated a causal relationship of genetic susceptibility to OSA on an increased risk of Barrett's esophagus (BE) and esophageal cancer (odds ratio [OR] = 1.32, 95% confidence interval [CI] = 1.07-1.62, p = 0.01), endometrial cancer (OR = 1.36, 95% CI = 1.16-1.60, p = 2.26E-04), and its endometrioid subtype (OR = 1.28, 95% CI = 1.04-1.59, p = 0.02). Multivariable MR, accounting for possible confounders like drinking and smoking, confirmed the causal relationships of OSA on BE and esophageal cancer, and endometrial cancer.

CONCLUSIONS

This study provided evidence regarding causal associations of OSA with higher risk of BE and esophageal cancer, and endometrial cancer.

The causal association between ankylosing spondylitis and endometrial cancer: a two-sample mendelian randomization study

INTRODUCTION

Multiple studies suggest a link between ankylosing spondylitis (AS) and endometrial cancer (EC), but causality is uncertain.

METHOD

We used genome-wide association studies (GWAS) data in a Mendelian randomization analysis, primarily inverse variance weighting, to investigate if genetically determined AS affects EC risk, with sensitivity analyses for heterogeneity and pleiotropy.

RESULTS

The IVW results showed a possible causal association between AS and EC (non-endometrioid histology) (OR = 1.05, 95% CI 1.01-1.1, P = 0.02), while there was no significant association between AS and the risks of EC (endometrioid histology) (OR = 0.99, 95% CI  0.97-1.01, P = 0.35) with EC (OR = 0.99, 95% CI 0.98-1.01, P = 0.34). The analysis results of MR Egger, weighted median, simple mode and weighted mode for AS and EC (non-endometrioid histology) were insignificant. No statistically significant heterogeneity or horizontal pleiotropy was detected.

CONCLUSIONS

This MR analysis did not reveal a substantial association between AS and overall EC or EC of endometrioid histology. Conversely, a significant causal connection between AS and non-endometrioid histology EC was identified. Additional research to are needed to explore the mechanisms of the relationship between AS and EC with the non-endometrioid subtype.

The role of sleep traits in prostate, endometrial, and epithelial ovarian cancers: An observational and Mendelian randomisation study

Background

Sleep traits may influence cancer risk; however, their associations with prostate (PCa), endometrial (ECa), and epithelial ovarian (EOCa) cancer remain unclear.

Methods

We conducted an observational analysis using the UK Biobank cohort and a two-sample Mendelian randomisation (MR) analysis to investigate the association of six sleep traits-duration, chronotype, insomnia, daytime napping, daytime sleepiness, and snoring-with PCa, ECa, and EOCa risk. Cox proportional hazards models were used for the observational analysis, while the inverse variance-weighted (IVW) method was applied in MR, with multiple sensitivity analyses. A Bonferroni correction accounted for multiple testing.

Results

Among 8,608 PCa, 1,079 ECa, and 680 EOCa incident diagnoses (median follow-up: 6.9 years), snoring was associated with reduced EOCa risk (HR=0.78, 95%CI: 0.62-0.98), while daytime sleepiness was associated with increased EOCa risk (HR=1.23, 95%CI: 1.03-1.47). However, these associations were not confirmed in MR. MR suggested higher odds of PCa (OR IVW =1.05, 95%CI: 1.01-1.11) and aggressive PCa (OR IVW =1.10, 95%CI: 1.02-1.19) for evening compared to morning chronotype. None of the findings survived multiple testing correction.

Conclusion

Sleep traits were not associated with PCa, ECa, or EOCa risk, but evening chronotype may increase PCa risk. Further research is needed to verify this association and investigate potential underlying mechanisms.

Impact

The proposed results have potential utility in reproductive cancer prevention.

What is already known on this topic

Sleep traits have been implicated in cancer risk, but their associations with prostate, endometrial, and epithelial ovarian cancer remain unclear.

What this study adds

This study found suggestive evidence that an evening chronotype may be associated with an increased risk of overall and aggressive prostate cancer.

How this study might affect research practice or policy

Further research is needed to confirm the potential association between chronotype and prostate cancer risk, which could inform personalised cancer prevention strategies.

Gut microbiota, blood metabolites, & pan-cancer: a bidirectional Mendelian randomization & mediation analysis

We propose using Mendelian randomization analysis on GWAS data and MetaboAnalyst to model gut microbiota, metabolic pathways, blood metabolites, and cancer risk. We examined 473 gut microbiota, 205 pathways, 1400 metabolites, and 8 cancers. Results were validated through bidirectional two-sample Mendelian Randomization (MR), heterogeneity tests, and pathway enrichment, leading to a mediation pathway model. We identified 129 gut microbiota, 57 pathways, and 463 metabolites linked to cancer, and 34 significant plasma pathways. 15 microbiota, 8 pathways, and 58 metabolites implicated in multiple cancers. Eight plasma metabolic pathways are involved in the development of multiple types of cancer. Through Multivariate Mendelian Randomization (MVMR) and mediation analysis, we found 9 mediation pathways, offering novel targets and research directions for cancer pathogenesis and treatment.

A large-scale genome-wide association study on female genital tract polyps highlights role of DNA repair, cell proliferation, and cell growth

STUDY QUESTION

Can a large-scale genome-wide association study (GWAS) meta-analysis identify genomic risk loci and likely involved genes for female genital tract (FGT) polyps, provide insights into the biological mechanism underlying their development, and inform of potential overlap with other traits, including endometrial cancer?

SUMMARY ANSWER

GWAS meta-analysis of FGT polyps highlights potentially shared mechanisms between polyp development and cancerous processes.

WHAT IS KNOWN ALREADY

Small-scale candidate gene studies have focused on biological processes such as oestrogen stimulation and inflammation to clarify the biology behind FGT polyps. However, the exact mechanism for the development of polyps is still elusive. At the same time, a genome-wide approach, which has become the gold standard in complex disease genetics, has never been used to uncover the genetics of the FGT polyps.

STUDY DESIGN, SIZE, DURATION

We performed a GWAS meta-analysis including a total of 36 984 women with FGT polyps (International Classification of Diseases (ICD-10) diagnosis code N84) and 420 993 female controls (without N84 code) of European ancestry from the FinnGen study (11 092 cases and 94 394 controls), Estonian Biobank (EstBB, 14 008 cases and 112 799 controls), and the Pan-UKBB study (11 884 cases and 213 800 controls).

PARTICIPANTS/MATERIALS, SETTING, METHODS

GWAS meta-analysis and functional annotation of GWAS signals were performed to identify genetic risk loci and prioritize genes in associated loci. To explore associations with other traits, we performed a look-up of associated variants across multiple traits and health conditions, genetic correlation analysis, and phenome-wide association study (PheWAS) with ICD-10 diagnosis codes.

MAIN RESULTS AND THE ROLE OF CHANCE

Our GWAS meta-analysis revealed 16 significant (P < 5 × 10-8) genomic risk loci. Based on exonic variants in GWAS signals, we prioritized EEFSEC, ODF3, PRIM1, PLCE1, LRRC34/MYNN, EXO1, and CHEK2 which are involved in DNA repair, cell proliferation, and cell growth. Several of the identified genomic loci have previously been linked to endometrial cancer and/or uterine fibroids, highlighting the potentially shared mechanisms underlying tissue overgrowth and cancerous processes. Genetic correlation analysis revealed a positive correlation with body mass index and reproductive traits, that can be classified as symptoms or risk factors of endometrial polyps (EPs), whereas a negative correlation was observed between FGT polyps and both menopause (genetic correlation estimate (rg) = -0.29, SE = 0.08, P = 8.8×10-4) and sex hormone-binding globulin (SHBG) (rg = -0.22, SE = 0.04, P = 2.4×10-8). On the phenotypic level, the strongest associations were observed with endometriosis, uterine fibroids, and excessive, frequent, and irregular menstruation.

LARGE SCALE DATA

The complete GWAS summary statistics will be made available after publication through the GWAS Catalog (https://www.ebi.ac.uk/gwas/).

LIMITATIONS, REASONS FOR CAUTION

In this study, we focused broadly on FGT polyps and did not differentiate between the polyp subtypes. Considering the prevalence of FGT polyp subtypes, we assumed that most women included in the study had EPs. Further research on the expression profile of FGT polyps could complement the GWAS study to substantiate the functional importance of the identified variants.

WIDER IMPLICATIONS OF THE FINDINGS

The study findings have the potential to significantly enhance our understanding of the genetic mechanisms involved, paving the way for future functional follow-up, which in turn could improve the diagnosis, risk assessment, and targeted treatment options, since surgery is the only line of treatment available for diagnosed polyps.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by European Union through the European Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations were performed in the High-Performance Computing Center of the University of Tartu. The study was also supported by the Estonian Research Council (grant no. PRG1076 and MOBJD1056) and Horizon 2020 innovation grant (ERIN, grant no. EU952516). All the authors declared no conflict of interest.

A Swedish genome-wide haplotype association analysis identifies novel candidate loci associated with endometrial cancer risk

Genome-wide association studies [GWAS] have identified a limited number of endometrial cancer risk loci by analyzing single nucleotide polymorphisms [SNPs]. We hypothesized that analyzing haplotypes rather than SNPs could provide novel and more detailed information on genetic cancer susceptibility loci. To examine the association of a SNP or haplotype with endometrial cancer risk we performed a two-stage haplotype GWAS. The discovery GWAS included a sub-cohort of 1,116 Swedish endometrial cancer cases and 5,021 controls from previously published GWAS data. A sliding window analysis was employed with window sizes of 1-25 SNPs using a logistic regression model. The Swedish haplotype analysis identified 15 novel candidate risk loci (2q31.1, 4p16.1, 4p15.31, 6q13, 7p21.1, 9p13.3, 10q26.3, 11q21, 12q13.11, 13q12.11, 15q13.3, 16q24.3, 19q13.32, 20p12.3 and 22q13.2) with OR ranging from 1.6 to 3.3 and p-values from 4.25 × 10-8 to 9.86 × 10-15. A second replication haplotype analysis of the Swedish novel loci was performed using two cohorts from Belgium and Germany. In spite of small sample sizes in the replication cohorts, there was still support for most loci with positive ORs. In addition, the findings in the two European cohorts motivates further studies to search for founder haplotypes. These novel findings suggested that endometrial cancer loci, identified through haplotype analysis, conferred a higher risk compared to previous single-variant GWAS.

Causal relationships of gut microbiota and blood metabolites with ovarian cancer and endometrial cancer: a Mendelian randomization study

OBJECTIVES

The study aimed to investigate the causal relationships of gut microbiota (GM), ovarian cancer (OC), endometrial cancer (EC), and potential metabolite mediators using Mendelian randomization (MR) analysis.

METHODS

Bidirectional two-sample MR analysis and reverse MR analysis of GM on OC/EC were employed to determine the causal effects of GM on OC/EC and the mediating role of blood metabolites in the relationship between GM and OC/EC, with results validated through sensitivity analysis.

RESULTS

We identified 6 pathogenic bacterial taxa associated with OC, including Euryarchaeota, Escherichia-Shigella, FamilyXIIIAD3011group, Prevotella9, and two unknown genera. Christensenellaceae R.7group, Tyzzerella3, and Victivallaceae were found to be protective against OC. The increase in EC risk was positively associated with Erysipelotrichia, Erysipelotrichaceae, Erysipelotrichales, and FamilyXI. Dorea, RuminococcaceaeUCG014, and Turicibacter exhibited a negative correlation with the EC risk. A total of 26 and 19 blood metabolites related to GM were identified, showing significant correlations with OC and EC, respectively. Cytosine was found to be an intermediate metabolite greatly associated with EC and FamilyXI. In reverse MR analysis, the FamilyXIIIAD3011group exhibited a significant bidirectional causal relationship with OC.

CONCLUSION

Our study revealed causal relationships of GM and intermediate metabolites with OC/EC, providing new avenues for understanding OC/EC and developing effective treatment strategies.

Atlas of genetic and phenotypic associations across 42 female reproductive health diagnoses

The genetic background of many female reproductive health diagnoses remains uncharacterized, compromising our understanding of the underlying biology. Here, we map the genetic architecture across 42 female-specific health conditions using data from up to 293,618 women from two large population-based cohorts, the Estonian Biobank and the FinnGen study. Our study illustrates the utility of genetic analyses in understanding women's health better. As specific examples, we describe genetic risk factors for ovarian cysts that elucidate the genetic determinants of folliculogenesis and, by leveraging population-specific variants, uncover new candidate genes for uterine fibroids. We find that most female reproductive health diagnoses have a heritable component, with varying degrees of polygenicity and discoverability. Finally, we identify pleiotropic loci and genes that function in genital tract development (WNT4, PAX8, WT1, SALL1), hormonal regulation (FSHB, GREB1, BMPR1B, SYNE1/ESR1) and folliculogenesis (CHEK2), underlining their integral roles in female reproductive health.

Genetic Variations in CYP19A1 and SLCO1B1 Genes and Their Association with Endometrial Cancer Risk in the Taiwanese Population: A Case-Control Study

Endometrial cancer is the most common gynecologic malignancy in developed countries, and its incidence is rising globally. Genetic predisposition plays a significant role in modulating risk, particularly in Asian populations. In Taiwan, the burden of endometrial cancer has increased, highlighting the need to gain a better understanding of the genetic loci associated with this disease. This retrospective case-control study included 373 endometrial cancer patients and 3730 controls from the Taiwan Precision Medicine Initiative. Genotype data were obtained using the TWB 2.0 SNP chip. Statistical analyses were conducted using PLINK and SPSS, with logistic regression models assessing the associations between genetic variants and endometrial cancer risk. In this study, we identified two SNPs, rs17601876 in CYP19A1 and rs2900478 in SLCO1B1, that were associated with endometrial cancer. The AG/GG genotypes of rs17601876 showed a protective effect (OR = 0.743, p = 0.006), while the TA/AA genotypes of rs2900478 exhibited a nonsignificant trend toward an increased risk. Higher BMI, LDL, triglyceride, total cholesterol, and HbA1c, as well as lower HDL, were strongly associated with greater risk. Our findings demonstrated a protective role of rs17601876 in CYP19A1 and further showed its potential impact on estrogen biosynthesis. Genetic factors involved in endometrial cancer risk are an important issue. Further functional studies are needed to validate the present findings.

Cathepsins and their role in gynecological cancers: Evidence from two-sample Mendelian randomization analysis

Prior studies have reported connections between cathepsins (CTS) and gynecological cancers; however, the exact causal links are yet to be fully understood. Leveraging publicly accessible genome-wide association study summary datasets, we performed a two-sample bidirectional Mendelian randomization (MR) and multivariate MR (MVMR) analysis, with the inverse variance weighted (IVW) method as the primary approach. MR analysis demonstrated inverse associations between CTSB and cervical cancer (IVW: odds ratio [OR] = 0.9995, 95% confidence interval [CI] = 0.9991-0.9999, P = .0418), CTSE and ovarian cancer (IVW: OR = 0.9197, 95% CI = 0.8505-0.9944, P = .0358), CTSZ and ovarian cancer (IVW: OR = 0.9449, 95% CI = 0.8938-0.9990, P = .0459), CTSE and high grade serous ovarian cancer (IVW: OR = 0.8939, 95% CI = 0.8248-0.9689, P = .0063), and CTSZ and high grade serous ovarian cancer (IVW: OR = 0.9269, 95% CI = 0.8667-0.9913, P = .0268). A positive correlation was identified between CTSH and clear cell ovarian cancer (IVW: OR = 1.1496, 95% CI = 1.0368-1.2745, P = .0081). Nevertheless, subsequent adjustment for the false discovery rate revealed that none of the P-values retained statistical significance (PFDR > 0.05). MVMR analysis results elucidated that CTSZ was inversely associated with cervical cancer (IVW: OR = 0.9988, 95% CI = 0.9981-0.9996, P = .0022). Moreover, a positive association was noted between CTSF and cervical cancer (IVW: OR = 1.0007, 95% CI = 1.0000-1.0014, P = .0364), and similarly, between CTSS and cervical cancer (IVW: OR = 1.0005, 95% CI = 1.0000-1.0011, P = .0490). CTSO exhibited a positive association with non-endometrioid endometrial cancer (IVW: OR = 1.4405, 95% CI = 1.1864-1.7490, P < .001), and CTSH was positively associated with clear cell ovarian cancer (IVW: OR = 1.1167, 95% CI = 1.0131-1.2310, P = .0263). The MVMR analysis findings reveal that CTSZ emerges as a protective element against cervical cancer, whereas CTSF and CTSS represent risk factors for this disease. CTSO stands out as a risk factor for non-endometrioid endometrial cancer, and CTSH acts as a risk factor for clear cell ovarian cancer. This study elucidates causative connections between CTS and gynecological cancers, providing innovative insights for diagnostic and therapeutic optimization.

The length of night shift work is closely associated with cancer risk: A pan-cancer study of Mendelian randomization study

Night shift work (NSW) has been associated with cancer risk in animal studies, but epidemiological evidence remains insufficient and contradictory. This study sought to investigate the causal association between NSW and 13 common cancers using a two-sample Mendelian randomization (MR) study. Genetic variants associated with NSW were extracted from the UK Biobank and selected as instrumental variables (IVs). Genome-wide association study (GWAS) data for 13 cancers were obtained from relevant consortia and biobanks. Causality was estimated using inverse-variance weighted (IVW), MR-Egger, and weighted median (WM). Sensitivity analyses, including MR-Egger intercept tests, MR-PRESSO, leave-one-out analyses, and funnel plots, were conducted to detect pleiotropy and heterogeneity. A suggestive causal association was found between NSW duration and risks of cervical (IVW: p = 0.028) and gastric cancer (IVW: p = 0.011). No significant associations were observed for other cancers (p > 0.05). These findings suggest the need to reduce NSW duration and limit nocturnal light exposure to maintain circadian rhythms and mitigate cancer risks.

Risk Stratification for Endometrial Cancer Reveals Independent Contributions of Polygenic Risk and Body Mass Index

Background

Obesity is a major risk factor for endometrial cancer, but it is unknown whether it impacts the association between genetic risk and endometrial cancer. We incorporated polygenic risk score and epidemiological risk factors in the prediction of and investigated associations of BMI and polygenic risk score with endometrial cancer risk.

Methods

We generated polygenic risk score for endometrial cancer in 129,829 unrelated female participants of European ancestry (including 956 incident cases with endometrial cancer) in the UK Biobank and predicted endometrial cancer using endometrial cancer polygenic risk score and established epidemiological risk factors, including BMI. We evaluated the performance of endometrial cancer prediction models by odds ratios and area under the receiver operating characteristic curves (AUCs) to using logistic regression. Individual and joint associations of BMI and polygenic risk score with endometrial cancer were assessed using Cox proportional hazards models.

Results

An integrated model incorporating both polygenic risk score and epidemiological risk factors achieved a modest, but statistically significant, improvement in predicting endometrial cancer status compared with the model that included epidemiologic risk factors alone (AUC = 0.74 versus 0.73; P = 3.98 × 10 -5 ). Obese participants (BMI ≥ 30 kg/m 2 ) in the top polygenic risk tertile had the highest endometrial cancer risk. We observed independent effects of genetic risk and BMI on endometrial cancer risk.

Conclusion

Integrating polygenic risk score with epidemiological risk factors may offer insights into population stratification for endometrial cancer susceptibility. Higher endometrial cancer polygenic risk is associated with endometrial cancer, irrespective of BMI.

The causal relationship between the gut microbiota and endometrial cancer: a mendelian randomization study

BACKGROUND

Gut microbiota is associated with endometrial cancer (EC); however, the causal relationship remains unexplored. This study attempted to explore the relationship between gut microbiota and EC using Mendelian randomization (MR) methods.

METHODS

In this two-sample MR analysis, we used MiBioGen's gut microbiota data as the exposure and three datasets from European populations with EC as the outcome. The EC datasets included general EC, endometrioid histology, and non-endometrioid histology. Single nucleotide polymorphism (SNP) was used as the instrumental variable. Inverse variance weighted (IVW), multiplicative random effects IVW (MRE-IVW), Maximum likelihood (ML), MR Egger, MR-PRESSO, and the weighted median were used to perform MR analysis. Sensitivity analysis was conducted to assess the reliability of the results.

RESULTS

In this MR analysis of three EC datasets, specific gut microbiota were identified as potentially associated with different pathological types of EC. For general EC (ID: ebi-a-GCST006464), Family.Acidaminococcaceae (OR = 1.23, 95%CI: 1.02-1.48) and genus.Butyrivibrio (OR = 1.08, 95%CI: 1.01-1.16) were identified as risk factors, while genus.Ruminococcaceae UCG014 (OR = 0.82, 95%CI: 0.69-0.98) and genus.Turicibacter (OR = 0.84, 95%CI: 0.73-0.97) appeared to have protective effects. For endometrioid histology EC (ID: ebi-a-GCST006465), Family.Acidaminococcaceae (OR = 1.27, 95%CI: 1.01-1.59) and genus.Butyrivibrio (OR = 1.10, 95%CI: 1.01-1.19) were identified as risk factors, while several microbiota, including Family.Lactobacillaceae, genus.Coprococcus3, genus.Dorea, genus.Flavonifractor, genus.Lactobacillus, genus.Paraprevotella, and genus.Turicibacter, were identified as protective factors. For non-endometrioid histology EC (ID: ebi-a-GCST006466), Family.Rhodospirillaceae (OR = 1.41, 95%CI: 1.01-1.96) and genus.Peptococcus (OR = 1.43, 95%CI: 1.07-1.91) were identified as risk factors, while no significant protective factors were identified.

CONCLUSIONS

This two-sample MR study has identified gut microbiota with potential causal relationships with EC, varying by pathological type. These findings provide new insights into the pathogenesis of EC and suggest directions for future research on diagnosis and treatment strategies.

Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

Aging can be understood as a consequence of the declining force of natural selection with age. Consistent with this, the antagonistic pleiotropy theory of aging proposes that aging arises from trade-offs that favor early growth and reproduction. However, evidence supporting antagonistic pleiotropy in humans remains limited. Using Mendelian Randomization (MR), we demonstrated that later ages of menarche or first childbirth were genetically associated with longer parental lifespan, decreased frailty index, slower epigenetic aging, later menopause, and reduced facial aging. Moreover, later menarche or first childbirth were also genetically associated with a lower risk of several age-related diseases, including late-onset Alzheimer's disease (LOAD), type 2 diabetes, heart disease, essential hypertension, and chronic obstructive pulmonary disease (COPD). We validated the associations between the age of menarche, childbirth, and the number of childbirths with several age-related outcomes in the UK Biobank by conducting regression analysis of nearly 200,000 subjects. Our results demonstrated that menarche before the age 11 and childbirth before 21 significantly accelerated the risk of several diseases, and almost doubled the risk for diabetes, heart failure, and quadrupled the risk of obesity, supporting the antagonistic pleiotropy theory. We identified 126 significant single nucleotide polymorphisms (SNPs) that influenced age-related outcomes, some of which were involved in known longevity pathways, including IGF1, growth hormone, AMPK, and mTOR signaling. Our study also identified higher BMI as a mediating factor in causing the increased risk of certain diseases, such as type 2 diabetes and heart failure, in women with early menarche or early pregnancy, emphasizing the importance of the thrifty gene hypothesis in explaining in part the mechanisms behind antagonistic pleiotropy. Our study highlights the complex relationship between genetic legacies and modern diseases, emphasizing the need for gender-sensitive healthcare strategies that consider the unique connections between female reproductive health and aging.

The Multi-Kinase Inhibitor GZD824 (Olverembatinib) Shows Pre-Clinical Efficacy in Endometrial Cancer

OBJECTIVE

Endometrial cancer is one of the few cancers for which mortality is still increasing. A lack of treatment options remains a major challenge, particularly for some subtypes of the disease. GZD824, also known as olverembatinib, is a multi-kinase inhibitor previously investigated in clinical trials for chronic myeloid leukaemia and Ph+ acute lymphoblastic leukaemia as a BCR-ABL inhibitor. This study aimed to investigate the pre-clinical efficacy of GZD824 for the treatment of EC.

METHODS

Here, we undertook pre-clinical evaluation of GZD824 in seven endometrial cancer cell lines (HEC-1-A, HEC-1-B, MFE296, RL95-2, Ishikawa, KLE and ARK-1), one normal immortalised endometrium derived cell line (E6E7hTERT) and primary mesothelial and fibroblast cells isolated from normal omentum samples.

RESULTS

GZD824 inhibited the proliferation of all endometrial cancer cell lines, which were significantly more sensitive to GZD824 compared to normal cells (p = 0.030). GZD824 significantly inhibited migration in Ishikawa (endometrioid) and ARK1 (serous) endometrial cancer cell lines and significantly inhibited invasion in the ARK1 cells. Whole transcriptome regulation following two doses (0.1 and 1 μM) of GZD824 in Ishikawa and ARK1 cells was investigated via RNA-seq, and key components of enriched pathways were investigated at the translational level. Key pathways altered included ROR1/Wnt, GCN2-ATF4, epithelial to mesenchymal transition (EMT) and PI3K-AKT.

CONCLUSION

Together, these studies support further investigation of GZD824 as a potential therapeutic agent in endometrial cancer, potentially in combination with immune checkpoint inhibitors.

Percentage of fat in milk consumption and risk of six cancers: a Mendelian randomization study

Background

The causal relationship between percentage of fat in milk consumption and cancer risk lacks sufficient investigation. The purpose of this study was to explore whether the percentage of fat in milk consumption is a factor that affects the risk variation of several common types of cancer.

Methods

Mendelian randomization (MR) was performed to estimate the unconfounded causal relationship between the percentage of fat in milk consumption and the risk of six cancers related to milk intake, as well as to assess the associations between body fat percentage and these cancers. Data corresponding to the percentage of fat in milk consumption (n=411,503), body fat percentage (n=401,772), breast cancer (n=139,274), ovarian cancer (n=66,450), endometrial cancer (n=121,885), colorectal cancer (n=32,072), prostate cancer (n=140,254), and bladder cancer (n=373,295) were obtained from the Integrative Epidemiology Unit (IEU) or the genome-wide association study (GWAS) Catalog databases. The primary analytical strategy employed the inverse-variance weighted (IVW) method. Sensitivity analysis, including assessments of heterogeneity and pleiotropy, was conducted to assess the robustness of the findings.

Results

The percentage of fat in milk consumption only exhibited a causal relationship with breast cancer (β=2.993, P=0.01). The study identified significant causal effects of body fat percentage on the risk of several cancers, including ovarian cancer (β=0.225, P=0.002), endometrial cancer (β=0.669, P<0.001), and colorectal cancer (β=0.344, P<0.001), as well as a protective effect on prostate cancer (β=-0.104, P=0.046). Sensitivity analysis demonstrated that the findings were robust.

Conclusions

Our study findings indicated that a higher percentage of fat in milk consumption was associated with an increased risk of breast cancer, providing valuable insights for cancer prevention strategies among the European population.

HNF1B polymorphisms and endometrial cancer risk: validation of identified loci and evaluation of novel variants

BACKGROUND

This study aimed to validate HNF1B single nucleotide polymorphisms (SNPs) associated with endometrial cancer risk in a Chinese Han population and explore novel SNPs. Our findings enhance the understanding of genetic components and are crucial for detection strategies and personalized medicine.

METHODS

We genotyped four HNF1B SNPs in 637 patients and 667 controls using Agena MassARRAY. Logistic regression calculated odds ratios (ORs) and 95% CI. Forest plots visualize stratified analyses. Multiple comparisons tested genetic loci-clinical indicator associations.

RESULTS

The study confirmed that rs4430796 (A>G) reduced endometrial cancer risk (OR = 0.83, 95% CI: 0.70-0.99, p = 0.041). Additionally, novel HNF1B mutations were associated with endometrial cancer risk: rs7405776 in individuals under the age of 55 (OR = 047, 95% CI: 0.25-0.91, p = 0.025) and nonsmokers (OR = 0.42, 95% CI: 0.23-0.75, p = 0.004), and rs11651755 in drinkers (OR = 0.39, 95% CI: 0.17-0.90, p = 0.027) and nonsmokers (OR = 0.43, 95% CI: 0.23-0.81, p = 0.009). The SNP rs4430796 was also associated with the CA125 level (p < 0.05).

CONCLUSION

HNF1B polymorphisms influence endometrial cancer risk in the Chinese Han population. Further studies are needed to explore the functional roles and clinical practicality of these SNPs.

Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study

Background

Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women.

Methods

Differentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation.

Results

We have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples.

Conclusion

This analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC.

Dostarlimab: A promising new PD-1 inhibitor for cancer immunotherapy

OBJECTIVE

Dostarlimab, a humanized monoclonal PD-1 blocking antibody, is being tested as a cancer therapy in this review. Specifically, it addresses mismatch repair failure in endometrial cancer and locally progressed rectal cancer patients.

DATA SOURCES

A thorough database search found Dostarlimab clinical trials and studies. Published publications and ongoing clinical trials on Dostarlimab's efficacy as a single therapy and in conjunction with other medicines across cancer types were searched.

DATA SUMMARY

The review recommends Dostarlimab for endometrial cancer mismatch repair failure, as supported by GARNET studies. The analysis also highlights locally advanced rectal cancer findings. In the evolving area of cancer therapy, immune checkpoint inhibitors including pembrolizumab, avelumab, atezolizumab, nivolumab, and durvalumab were discussed.

CONCLUSIONS

Locally advanced rectal cancer patients responded 100% to Dostarlimab. Many clinical trials, including ROSCAN, AMBER, IOLite, CITRINO, JASPER, OPAL, PRIME, PERLA, and others, are investigating Dostarlimab in combination treatment. This research sheds light on Dostarlimab's current and future possibilities, in improving cancer immunotherapy understanding.

Causal relationship between affect disorders and endometrial cancer: a Mendelian randomisation study

BACKGROUND

The aim was to assess the causal relationship between depression and anxiety disorders and endometrial cancer.

METHOD

We performed two-sample Mendelian randomisation analysis using summary statistics from genome-wide association studies to assess associations of major depressive disorder, anxiety and stress-related disorders with endometrial cancer. The genome-wide association studies(GWASs) data were derived from participants of predominantly European ancestry included in the Genome-wide Association Research Collaboration. Inverse variance-weighted, MR-Egger and weighted median MR analyses were performed, together with a range of sensitivity analyses.

RESULTS

Mendelian randomisation analysis showed no statistically significant genetic responsibility effect of anxiety and stress-related disorders on any pathological type of endometrial cancer. Only the effect of major depressive disorder under the inverse variance weighting method increasing the risk of endometrial endometrial cancer (effect 0.004 p = 0.047) and the effect of major depressive disorder under the MR-Egger method decreasing endometrial cancer of all pathology types (effect -0.691 p = 0.015) were statistically significant. Other Mendelian randomisation analyses did not show a statistically significant effect.

CONCLUSION

Major depressive disorder(MDD), anxiety and stress-related disorders(ASRD) are not genetically responsible for endometrial cancer. We consider that emotional disorders may affect endometrial cancer indirectly by affecting body mass index. This study provides us with new insights to better understand the aetiology of endometrial cancer and inform prevention strategies.

Germline copy number variants and endometrial cancer risk

Known risk loci for endometrial cancer explain approximately one third of familial endometrial cancer. However, the association of germline copy number variants (CNVs) with endometrial cancer risk remains relatively unknown. We conducted a genome-wide analysis of rare CNVs overlapping gene regions in 4115 endometrial cancer cases and 17,818 controls to identify functionally relevant variants associated with disease. We identified a 1.22-fold greater number of CNVs in DNA samples from cases compared to DNA samples from controls (p = 4.4 × 10-63). Under three models of putative CNV impact (deletion, duplication, and loss of function), genome-wide association studies identified 141 candidate gene loci associated (p < 0.01) with endometrial cancer risk. Pathway analysis of the candidate loci revealed an enrichment of genes involved in the 16p11.2 proximal deletion syndrome, driven by a large recurrent deletion (chr16:29,595,483-30,159,693) identified in 0.15% of endometrial cancer cases and 0.02% of control participants. Together, these data provide evidence that rare copy number variants have a role in endometrial cancer susceptibility and that the proximal 16p11.2 BP4-BP5 region contains 25 candidate risk gene(s) that warrant further analysis to better understand their role in human disease.

[Causal Relationship Between Components of Metabolic Syndrome and Endometrial Carcinoma]

Objective

To investigate the causal associations between components of metabolic syndrome (MetS) and endometrial carcinoma using Mendelian randomization (MR).

Methods

Data mining of the Genome-Wide Association Studies (GWAS) database was performed, with the exposure factors being MetS components (lipids, blood pressure, blood glucose, and obesity) and the outcome factor being endometrial carcinoma. MR analyses were performed with the help of regression models, including MR-Egger method, weighted median method, and inverse variance weighted (IVW) method, and the causal relationship between MetS components and endometrial carcinoma was evaluated by odds ratio (OR). Reverse MR analysis was performed for the MetS components found to have a causal relationship with endometrial carcinoma in the forward MR analysis.

Results

After applying Benjamini-Hochberg correction, IVW results showed a causal relationship between multiple MetS components (obesity, lipids, blood pressure, and blood glucose) and endometrial carcinoma. Specifically, the three components of obesity, including body mass index, overweight, and percentage of body fat, were causally associated with an increased risk of endometrial carcinoma (P<0.001, OR>1). In blood lipids, high cholesterol levels (P<0.001, OR<1), high triglyceride levels, and high phospholipid levels were causally associated with a reduced risk of endometrial carcinoma (P<0.05, OR<1). Regarding blood pressure, heart disease, atherosclerosis, and stroke were causally associated with a reduced risk of endometrial carcinoma (P<0.05, OR<1). Regarding blood glucose, low fasting insulin levels, type 1 diabetes mellitus, insulin resistance, and high glycated hemoglobin levels were causally associated with a reduced risk of endometrial carcinoma (P<0.05, OR<1), while type 2 diabetes mellitus and high fasting insulin levels were causally associated with an increased risk of endometrial carcinoma (P<0.05, OR>1). Reverse MR analysis did not produce any evidence for a reverse causality between the above positive MetS components and endometrial carcinoma.

Conclusion

The MR study suggests that obesity and type 2 diabetes mellitus are risk factors for endometrial carcinoma, while other MetS components, including hyperlipidemia, cardiovascular diseases, insulin resistance, and complications of diabetes mellitus, are protective factors for endometrial carcinoma. Further research is needed to clarify the association between MetS and endometrial carcinoma and to further explore the underlying mechanisms involved.

Causal relationship between cancer and immune cell traits: A two-sample mendelian randomization study

Background

Observational studies provide evidence of correlations between cancer and the immune system. Previous research has established associations between immune traits and the propensity for developing certain cancers. However, a systematic exploration of these connections remains largely uncharted. Therefore, further investigation is needed to examine the causal association between cancer and immune cell traits using Mendelian randomization (MR) approach.

Methods

We identified genetic instruments for breast cancer (BC), lung cancer (LC), endometrial cancer (EC), ovarian cancer (OC), prostate cancer (PC), and their subtype cancers to investigate their potential causal impact on immune traits. Data on cancer and immune cell traits were obtained from the IEU Open GWAS project. To assess whether these five cancer types and subtype cancers have a causal association with immune cell traits, we conducted two-sample MR analyses. Additionally, we conducted bidirectional MR analyses to examine the direction of causal relationships and adjusted for potentially related pleiotropy through multivariable MR analysis.

Results

We have identified several causal relationships between different types of cancer and immune traits. We found that breast cancer may influence 49 immune cell traits, endometrial cancer may influence 38, lung cancer may influence 25, ovarian cancer may influence 19, and prostate cancer may influence 28. Among these, breast cancer and lung cancer were associated with four common immune traits: CD25 on IgD- CD38dim, CD25 on sw mem, CD24 on IgD- CD38-, and CD25 on IgD- CD38-. Lung cancer and prostate cancer shared four immune traits: CD25 on IgD+ CD24+, CD25 on IgD+ CD38-, CD66b on CD66b++ myeloid cell, DN (CD4-CD8-) AC. Endometrial cancer and ovarian cancer shared two immune traits: TD DN (CD4-CD8-) %DN, EM DN (CD4-CD8-) %DN. Breast cancer and endometrial cancer shared one immune trait: CD20 on IgD- CD38dim. Endometrial cancer and prostate cancer shared one immune trait: CCR2 on myeloid DC. Lastly, breast cancer, lung cancer, and prostate cancer shared one immune trait: CD25 on CD24+ CD27+. Additionally, we identified specific immune traits that may serve as protective or risk factors for cancers. We found 14 immune traits may influence breast cancer, 9 immune traits may influence endometrial cancer, 22 immune traits may influence lung cancer, 9 immune traits may influence ovarian cancer, and 14 immune traits may influence prostate cancer. Among these, breast cancer and prostate cancer shared three immune traits: HLA DR++ monocyte %monocyte, HLA DR on plasmacytoid DC, and HLA DR on DC. Lung cancer and ovarian cancer shared one immune trait: CD62L- monocyte %monocyte. Prostate cancer and endometrial cancer shared one immune trait: HLA DR on CD33dim HLA DR + CD11b+. Lastly, ovarian cancer and prostate cancer shared one immune trait: CD3 on resting Treg.

Conclusions

Our MR study suggests a potential relationship between immune traits and cancers, particularly highlighting 14 immune traits that are simultaneously influenced by two or three of five cancer types, while also indicating that 6 immune traits may simultaneously contribute to the development of two of the cancers. This elucidation enables us to reveal a significant involvement of immune traits in cancer progression, providing critical insights into how immune traits affect cancer susceptibility.

Genetic variation perspective reveals potential drug targets for subtypes of endometrial cancer

The study aims to identify potential drug targets for endometrial cancer (EC) subtypes through a Mendelian randomization (MR) approach, assessing their clinical relevance. We utilized genetic instruments for 4,907 plasma proteins from the deCODE Genetics study dataset, and data with EC (n = 12,906) from a genome-wide study (GWAS) meta-analysis in European populations for MR analyses. Complementary analyses included protein-protein interactions (PPI) network analysis, therapeutic efficacy evaluation, differential gene expression assessment, and prognosis evaluation. The expression levels of key drug targets were quantitatively measured at both the transcriptional and translational stages utilizing reverse transcription quantitative PCR (RT-qPCR) and immunohistochemistry (IHC). Additionally, we analyzed various clinicopathological features. Five drug targets for EC (CBR3, GSTO1, HHIP, IGF2R, and MMP10), seven for endometrioid subtypes (ACAP2, CBR3, GSTO1, HHIP, IGF2R, MMP10, and TLR2), and seven for non-endometrioid subtypes (CST3, DNAJB14, FSTL5, GMPR2, IFI16, MAPK9, and NEO1) were identified. Among these, IGF2R (OR = 1.165; 95% CI 1.067-1.272; p = 1.046 × 10- 2) and CST3 (OR = 0.523; 95% CI 0.339-0.804; p = 7.010 × 10- 3) were highlighted as key drug targets with causal evidence both at transcriptional and translational levels. This study preliminarily confirms that IGF2R and CST3 may serve as novel targets for the treatment of EC, providing a foundational reference for innovative clinical approaches to this disease.

GWAS and 3D chromatin mapping identifies multicancer risk genes associated with hormone-dependent cancers

Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.

Isoform-level analyses of 6 cancers uncover extensive genetic risk mechanisms undetected at the gene-level

Integrating genome-wide association study (GWAS) and transcriptomic datasets can help identify potential mediators for germline genetic risk of cancer. However, traditional methods have been largely unsuccessful because of an overreliance on total gene expression. These approaches overlook alternative splicing, which can produce multiple isoforms from the same gene, each with potentially different effects on cancer risk. Here, we integrate genetic and multi-tissue isoform-level gene expression data from the Genotype Tissue-Expression Project (GTEx, N = 108-574) with publicly available European-ancestry GWAS summary statistics (all N > 20,000 cases) to identify both isoform- and gene-level risk associations with six cancers (breast, endometrial, colorectal, lung, ovarian, prostate) and six related cancer subtype classifications (N = 12 total). Compared to traditional methods leveraging total gene expression, directly modeling isoform expression through transcriptome-wide association studies (isoTWAS) substantially increases discovery of transcriptomic mechanisms underlying genetic associations. Using the same RNA-seq datasets, isoTWAS identified 164% more significant unique gene associations compared to TWAS (6,163 and 2,336, respectively), with isoTWAS-prioritized genes enriched 4-fold for evolutionarily-constrained genes (P = 6.1 × 10-13). isoTWAS tags transcriptomic associations at 52% more independent GWAS loci compared to TWAS across the six cancers. Additionally, isoform expression mediates an estimated 63% greater proportion of cancer risk SNP heritability compared to gene expression when evaluating cis-genetic influence on isoform expression. We highlight several notable isoTWAS associations that demonstrate GWAS colocalization at the isoform level but not at the gene level, including, CLPTM1L (lung cancer), LAMC1 (colorectal), and BABAM1 (breast). These results underscore the critical importance of modeling isoform-level expression to maximize discovery of genetic risk mechanisms for cancers.

Using Genetics to Assess the Role of Acetate in Ischemic Heart Disease, Diabetes, and Sex-Hormone-Related Cancers: A Mendelian Randomization Study

BACKGROUND

Acetate, a short-chain fatty acid, has gained attention for its contrasting roles, with evidence suggesting it may offer cardiovascular protection but also promote cancer, particularly those involving sex hormones. However, these influences have been scarcely assessed in epidemiological research.

OBJECTIVE

To investigate the relationship between acetate and ischemic heart disease (IHD), diabetes, and cancers related to sex hormones.

METHODS

Mendelian randomization (MR) was used to assess potential causal effects, selecting genetic variants without linkage disequilibrium (r2 < 0.001) and with genome-wide significance for acetate (p < 5 × 10-8). These variants were applied to large genome-wide association studies (GWAS) for ischemic heart disease (IHD; up to 154,373 cases), diabetes (109,731 cases), and five sex-hormone-related cancers (breast, colorectal, prostate, ovarian, and endometrial cancers, ranging from 8679 to 122,977 cases). We employed various methods for analysis, including penalized inverse variance weighting (pIVW), inverse variance weighting, weighted mode, and weighted median.

RESULTS

This study indicates that acetate may be associated with a lower risk of ischemic heart disease (IHD), with an odds ratio (OR) of 0.62 per standard deviation (SD) increase in acetate and a 95% confidence interval (CI) of 0.39 to 0.98. Additionally, acetate was linked to a higher breast cancer risk, with an OR of 1.26 and a 95% CI ranging from 1.08 to 1.46. This association remained robust across multiple sensitivity analyses.

CONCLUSIONS

Acetate, along with factors that influence its activity, may serve as possible targets for breast cancer treatment and possibly IHD, offering opportunities for new drug development.

Circulating Phylloquinone and the Risk of Four Female-Specific Cancers: A Mendelian Randomization Study

BACKGROUND

Observational studies have linked vitamin K and cancer, but the causality of this association remains unknown. This Mendelian randomization (MR) study aims to investigate the association between circulating phylloquinone (vitamin K1) levels and four female-specific cancers.

METHODS

We used four single-nucleotide polymorphisms (SNPs) to instrument phylloquinone, with the reported F-statistic 16.00-28.44 for all variants. SNP-outcome associations were obtained from consortia meta-analyses, UK Biobank, and the FinnGen database (up to 145,257/419,675, 27,446/362,324, 15,181/591,477, and 2211/320,454 cases/controls for breast, ovarian, endometrial, and cervical cancer, respectively). Analyses were conducted using five complementary MR methods including pleiotropy robust approaches. The MR Egger intercept test, MR PRESSO global test and leave-one-out analyses were used to test for and identify pleiotropic variants.

RESULTS

The relevance of the instrument was validated by positive control analyses on coagulation factor IX (p = 0.01). However, the main MR analysis and all sensitivity analyses were consistently supportive of a null association between phylloquinone and all four cancers (p > 0.05 for all analyses, across all methods). MR-PRESSO did not detect outlying variants, and there was no evidence of horizontal pleiotropy relating to any cancer outcome (pintercept > 0.26 for all).

CONCLUSIONS

We found no evidence for an association between genetically predicted circulating phylloquinone levels and the risk of four female-specific cancers.

Unraveling the causal association between lifestyle and metabolic factors with endometrial cancer: evidence from a Mendelian randomization study

BACKGROUND

Endometrial carcinoma (EC) remain a malignancy with incompletely understood risk factors. To address this knowledge gap, we employed mendelian randomization study to investigate potential protective and risk elements associated with endometrial cancer.

METHODS

We conducted a two-sample Mendelian randomization (MR) study using genetic association data for overall EC and its subtypes from a large-scale genome-wide association study (GWAS). This GWAS encompassed 12,906 EC patients and 108,979 healthy controls. The EC cases were further categorized into 8758 endometrioid and 1230 non-endometrioid subtypes. To serve as instrumental variables, we identified independent genetic variants strongly associated with 5 lifestyle factors and 14 metabolic factors from relevant GWASs. Subsequently, we conducted univariable Mendelian randomization (MR) analyses.

RESULTS

Our study revealed the relationship among EC with lifetime smoking index (OR: 1.43; 95% CI 1.05-1.96), frequency of alcohol consumption (OR:1.23; 95% CI 1.04-1.45), body mass index (BMI) (OR:1.82; 95% CI 1.64-2.01), type 2 diabetes mellitus (T2DM) (OR:1.06; 95% CI 1.00-1.12), and fasting insulin (OR:1.97; 95% CI 1.30-2.98). Conversely, inverse associations with EC were observed for education level (OR:0.72, 95% CI 0.62-0.83), moderate-level physical exercise (OR 0.35, 95% CI 0.15-0.84), and low-density lipoproteins (LDL) (OR 0.91, 95% CI 0.84-0.99).

CONCLUSIONS

Our findings underscore a causal association between genetically predicted lifetime smoking index, alcohol intake frequency, BMI, T2DM, and fasting insulin with EC risk. Furthermore, our study highlights the potential protective effects of a high education level, moderate-intensity physical exercise, and LDL reduction against EC risk. This MR analysis provided valuable insights into underlying EC risk mechanisms and paved new ways for EC prevention strategies.

Investigating the genetic causal relationship between breast cancer and endometrial cancer: A two-sample Mendelian randomization study

Observational studies have consistently shown a correlation between breast cancer (BC) and endometrial cancer (EC). Despite these findings, the causal relationship between these cancers has not been clearly defined. This research employed a bidirectional two-sample Mendelian randomization to explore the genetic causality between BC and EC. Genetic instruments for BC were derived from the Breast Cancer Association Consortium genome-wide association studies summary statistics, while for EC, data were sourced from the Endometrial Cancer Association Consortium, the Epidemiology of Endometrial Cancer Consortium, and the UK Biobank. The primary analytical method was inverse-variance weighted. Additional analyses, such as MR-Egger and weighted median, were conducted to validate the robustness of our findings from multiple perspectives. The MR-Egger intercept test was conducted to examine potential pleiotropy, whereas Cochrane Q test was implemented to assess heterogeneity. A leave-one-out analysis was conducted to assess the sensitivity of the observed association. Our analysis identified a bidirectional genetic causal relationship between estrogen receptor-positive breast cancer (ER+BC) and EC. Inverse-variance weighted analysis indicated an odds ratio of 1.0686 (95% confidence interval: 1.0029-1.1386, P = .0403) from ER+BC to EC and an odds ratio of 1.0692 (95% confidence interval: 1.0183-1.1225, P = .0071) from EC to ER+BC. No significant horizontal pleiotropy was detected. This study confirms a bidirectional genetic link between ER+BC and EC, suggesting shared genetic etiologies and possibly linked pathophysiological pathways. Understanding the genetic interplay between ER+BC and EC can enhance strategies for the precise prevention and screening of these prevalent cancers, potentially leading to improved clinical outcomes and management of secondary primary malignancies.

Burden of uterine cancer in China from 1990 to 2021 and 15-year projection: a systematic analysis and comparison with global levels

OBJECTIVE

Uterine cancer (UC) is one of the prevalent malignancies in the female reproductive system. Estimating the burden trends of UC is crucial for developing effective prevention strategies at the national level. However, there has been no comprehensive analysis of the UC burden in China. We focused on the evaluation of the burden trends of UC in China over the past 32 years to provide a 15-year projection, comparing it with global levels.

METHODS

Data on incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were extracted from Global Burden of Disease (GBD) 2021 to describe the burden of UC in China. Joinpoint regression analysis was employed to describe the temporal trends of UC in China and globally over the past 32 years. A Bayesian age-period-cohort model was utilized to predict the trends of UC in the next 15 years. Spearman correlation analysis was used to compare the relationship between ASIR, ASPR, ASMR, ASDR, and SDI in UC in China and globally. Changes in ASMR and ASDR in UC caused by high BMI in China and globally from 1990 to 2021 were explored.

RESULTS

In 2021, the age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDR) of UC in China were 6.65, 46.52, 1.24, and 37.86 (per 100,000 population) respectively. Compared to 1990, the ASMR and ASDR decreased by 48.63% and 48.15% respectively, while the ASIR and ASPR increased by 17.79% and 37.67% respectively. Globally, the burden of UC followed a similar trend in China, with increasing ASIR and ASPR, and decreasing ASMR and ASDR, although the magnitude of increase and decrease was smaller than in China. Joinpoint regression analysis results showed an overall upward trend in ASIR and ASPR for both China and global UC, while an overall downward trend was observed in ASMR and ASDR. Age-specific analysis revealed that during the period from 1990 to 2021, the age groups with the highest incidence, prevalence, mortality, and DALYs for UC in China generally occurred at earlier ages compared to the global pattern. It is projected that over the next 15 years, the burden of UC in China will continue to increase at a higher rate than the global level. Spearman correlation analysis showed that ASIR and ASPR of UC in China and the world were significantly positively correlated with SDI (p < 0.05), and ASMR and ASDR were significantly negatively correlated with SDI (p < 0.001). High BMI is a risk factor affecting the mortality rate and DALYs of UC in both China and globally, with the increase in ASMR and ASDR due to high BMI being greater in China than globally.

CONCLUSION

The incidence and prevalence burden of UC among Chinese and global women have shown an increasing trend over the past 32 years, while the mortality and DALYs have decreased. The projected burden of UC in China is anticipated to continue rising at a higher rate than the global level over the next 15 years. Given the large population in China, the government needs to strengthen screening and prevention strategies to mitigate the burden of UC.

Circulating inflammatory and immune response proteins and endometrial cancer risk: a nested case-control study and Mendelian randomization analyses

BACKGROUND

Inflammation and immune dysregulation are hypothesized contributors to endometrial carcinogenesis; however, the precise underlying mechanisms remain unclear.

METHODS

We measured pre-diagnostically 152 plasma protein biomarkers in 624 endometrial cancer case-control pairs nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Odds ratios (ORs) were estimated using conditional logistic regression, accounting for confounding and multiple comparisons. Proteins considered as associated with endometrial cancer risk were further tested in a two-sample Mendelian randomization (MR) analysis using summary data from the UK Biobank (n = 52,363) and the Endometrial Cancer Association Consortium (12,270 cases and 46,126 controls).

FINDINGS

In the EPIC nested case-control study, IL-6 [OR per NPX (doubling of concentration) = 1.28 (95% confidence interval (CI) 1.03-1.57)], HGF [1.48 (1.06-2.07)], PIK3AP1 [1.22 (1.00-1.50)] and CLEC4G [1.52 (1.00-2.32)] were positively associated; HSD11B1 [0.67 (0.49-0.91)], SCF [0.68 (0.49-0.94)], and CCL25 [0.80 (0.65-0.99)] were inversely associated with endometrial cancer risk; all estimates had multiple comparisons adjusted P-value > 0.05. In complementary MR analysis, IL-6 [OR per inverse-rank normalized NPX = 1.19 (95% CI 1.04-1.36)] and HSD11B1 [0.91 (0.84-0.99)] were associated with endometrial cancer risk.

INTERPRETATION

Altered IL-6 signalling and reduced glucocorticoid activity via HSD11B1 might play important roles in endometrial carcinogenesis.

FUNDING

Funding for IIG_FULL_2021_008 was obtained from Wereld Kanker Onderzoek Fonds (WKOF), as part of the World Cancer Research Fund International grant programme; Funding for INCA_15849 was obtained from Institut National du Cancer (INCa).

Associations between serum metabolites and female cancers: A bidirectional two-sample mendelian randomization study

Female cancers, especially breast, ovarian, cervical, and endometrial cancers, constitute a major threat to women's health worldwide. In view of the complex genetic background of cancers cannot be fully explained with current genetic information, we used a bidirectional two-sample mendelian randomization approach to explore the causal associations between serum metabolites and four major female cancers-breast, ovarian, cervical, and endometrial cancers. We analyzed the metabolites dataset from the Canadian Longitudinal Study of Aging and cancer datasets from the 10th round of the Finngen project. Replication analyses was performed with Cancer Association Consortium and Leo's studies. Instrumental variables were analyzed using methods including the Wald ratio, inverse-variance weighted, MR-Egger, and weighted median. To ensure robustness, sensitivity analyses were performed using Cochrane's Q, Egger's intercept, MR-PRESSO, and leave-one-out methods. After meticulous analysis, we obtained levels of 3-hydroxyoleoylcarnitine, hexadecanedioate, tetradecanedioate, and carnitine C14 with robust causal associations with breast cancer, levels of 5alpha-androstan-3alpha,17beta-diol monosulfate (1), androstenediol (3beta,17beta) monosulfate (1), androsterone sulfate, and 5alpha-androstan-3beta,17beta-diol disulfate causal associations with endometrial cancer. The reverse analysis showed that breast, ovarian, and endometrial cancer and survival of breast and ovarian cancer were found to have causal relationships with 8, 5, 2, 6, and 3 metabolites, respectively. These insights underscore the potential roles of specific metabolites in the etiology of female cancers, providing new biomarkers for early detection, risk stratification, and disease progression monitoring. Further research could elucidate how these metabolites influence specific pathways in cancer development, offering theoretical foundations for prevention and treatment strategies.

Mendelian randomization analysis using multiple biomarkers of an underlying common exposure

Mendelian randomization (MR) analysis is increasingly popular for testing the causal effect of exposures on disease outcomes using data from genome-wide association studies. In some settings, the underlying exposure, such as systematic inflammation, may not be directly observable, but measurements can be available on multiple biomarkers or other types of traits that are co-regulated by the exposure. We propose a method for MR analysis on latent exposures (MRLE), which tests the significance for, and the direction of, the effect of a latent exposure by leveraging information from multiple related traits. The method is developed by constructing a set of estimating functions based on the second-order moments of GWAS summary association statistics for the observable traits, under a structural equation model where genetic variants are assumed to have indirect effects through the latent exposure and potentially direct effects on the traits. Simulation studies show that MRLE has well-controlled type I error rates and enhanced power compared to single-trait MR tests under various types of pleiotropy. Applications of MRLE using genetic association statistics across five inflammatory biomarkers (CRP, IL-6, IL-8, TNF-α, and MCP-1) provide evidence for potential causal effects of inflammation on increasing the risk of coronary artery disease, colorectal cancer, and rheumatoid arthritis, while standard MR analysis for individual biomarkers fails to detect consistent evidence for such effects.

Causal Relationship Between Mood Swing and Gynecological Disorders: A Mendelian Randomization Study

Background

Gynecological disorders are a wide range of health problems affecting the female reproductive system, which poses substantial health challenges worldwide. Increasing number of observational studies have associated mood instability to common female diseases, but the underlying causal relationship remains unclear. In this work, Mendelian randomization (MR) analysis was applied to explore the genetically predicted causal relationship of mood swings and several prevalent gynecological disorders.

Methods

Instrumental variables (IVs) of mood swings were selected from UK Biobank (UKB), with 204,412 cases and 247,207 controls being incorporated. The genetic variants for female disorders were obtained from genome-wide association studies (GWASs) and FinnGen consortium. To avoid biases caused by racial difference, only European population was included here. Five strong analytical methodologies were used to increase the validity of the results, the most substantial of which was the inverse variance weighting (IVW) method. Pleiotropy, sensitivity, and heterogeneity were assessed to strengthen the findings.

Results

We found mood swings was significantly positively associated with risk of endometrial cancer (OR= 2.60 [95% CI= 1.36, 4.95], P= 0.0037), cervical cancer (OR= 1.01[95% CI= 1.00,1.02], P= 0.0213) and endometriosis (OR= 2.58 [95% CI= 1.18, 5.60], P= 0.0170) by IVW method. However, there was no causal relationship between mood swing and ovarian cancer. No pleiotropy and heterogeneity existed and sensitivity tests were passed.

Conclusion

This study reveals that mood swing may serve as a genetically predicted causal risk factor for endometrial cancer, cervical cancer, and endometriosis in the European population, while no such association was observed for ovarian cancer. These findings make up for observational research's inherent limitations and may improve patient outcomes in the field of gynecological health. However, the study's focus on European populations may limit the applicability of these results globally.

Unravelling the molecular landscape of endometrial cancer subtypes: insights from multiomics analysis

BACKGROUND

Endometrial cancer (EC) as one of the most common gynecologic malignancies is increasing in incidence during the past 10 years. Genome-Wide Association Studies (GWAS) extended to metabolic and protein phenotypes inspired us to employ multiomics methods to analyze the causal relationships of plasma metabolites and proteins with EC to advance our understanding of EC biology and pave the way for more targeted approaches to its diagnosis and treatment by comparing the molecular profiles of different EC subtypes.

METHODS

Two-sample mendelian randomization (MR) was performed to investigate the effects of plasma metabolites and proteins on risks of different subtypes of EC (endometrioid and nonendometrioid). Pathway analysis, transcriptomic analysis, and network analysis were further employed to illustrate gene-protein-metabolites interactions underlying the pathogenesis of distinct EC histological types.

RESULTS

The authors identified 66 causal relationships between plasma metabolites and endometrioid EC, and 132 causal relationships between plasma proteins and endometrioid EC. Additionally, 40 causal relationships between plasma metabolites and nonendometrioid EC, and 125 causal relationships between plasma proteins and nonendometrioid EC were observed. Substantial differences were observed between endometrioid and nonendometrioid histological types of EC at both the metabolite and protein levels. The authors identified seven overlapping proteins (RGMA, NRXN2, EVA1C, SLC14A1, SLC6A14, SCUBE1, FGF8) in endometrioid subtype and six overlapping proteins (IL32, GRB7, L1CAM, CCL25, GGT2, PSG5) in nonendometrioid subtype and conducted network analysis of above proteins and metabolites to identify coregulated nodes.

CONCLUSIONS

Our findings observed substantial differences between endometrioid and nonendometrioid EC at the metabolite and protein levels, providing novel insights into gene-protein-metabolites interactions that could influence future EC treatments.

Genetic association of lipids and lipid-lowering drug target genes with Endometrial carcinoma: a drug target Mendelian randomization study

BACKGROUND

Aberrant lipid metabolism is intricately linked to the development of endometrial cancer, and statin lipid-lowering medications are regarded as promising adjunctive therapies for future management of this malignancy. This study employed Mendelian randomization (MR) to explore the causal association between lipid traits and endometrial cancer while assessing the potential impact of drug targets on lower lipids on endometrial cancer.

METHOD

Two-sample Mendelian randomization was employed to probe the causal association between lipid traits and endometrial carcinoma. Drug-target Mendelian randomization was also utilized to identify potential drug-target genes for managing endometrial carcinoma. In instances where lipid-mediated effects through particular drug targets were notable, the impacts of these drug targets on endometrial carcinoma risk factors were investigated to bolster the findings.

RESULT

No causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC was found in two-sample Mendelian randomization. In drug target Mendelian randomization, genetic modeling of apolipoprotein B (APOB) (OR [95%CI]=0.31, [0.16-0.60]; p=4.73e-04) and cholesteryl ester transfer protein (CETP) (OR [95%CI]=1.83, [1.38-2.43]; p=2.91e-05) genetic mimicry was associated with non-endometrioid carcinoma.

CONCLUSION

The results of our MR study revealed no causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC. Among the six lipid-lowering drug targets, we observed a significant association between lower predicted APOB levels and higher CETP levels with an increased risk of endometrioid carcinoma. These findings provide novel insights into the importance of lipid regulation in individuals with endometrial carcinoma, warranting further clinical validation and mechanistic investigations.

Association of glucagon-like peptide-1 receptor agonists with risk of cancers-evidence from a drug target Mendelian randomization and clinical trials

BACKGROUND

Glucagon-like peptide-1 receptor (GLP1R) agonists have been approved by Food and Drug Administration for management of obesity. However, the causal relationship of GLP1R agonists (GLP1RA) with cancers still unclear.

METHODS

The available cis-eQTLs for drugs target genes (GLP1R) were used as proxies for exposure to GLP1RA. Mendelian randomizations (MR) were performed to reveal the association of genetically-proxied GLP1RA with 14 common types cancer from large-scale consortia. Type 2 diabetes was used as positive control, and the GWASs data including 80 154 cases and 853 816 controls. Replicating the findings in the FinnGen study and then pooled with meta-analysis. Finally, all the related randomized controlled trails (RCTs) on GLP1RA were systematically searched from PubMed, Embase, and the Cochrane Library to comprehensively synthesize the evidence to validate any possible association with cancers.

RESULT

A total of 22 significant cis-eQTL single-nucleotide polymorphisms were included as genetic instrument. The association of genetically-proxied GLP1RA with significantly decreased type 2 diabetes risk [OR (95%)=0.82 (0.79-0.86), P <0.001], which ensuring the effectiveness of identified genetic instruments. The authors found favorable evidence to support the association of GLP1RA with reduced breast cancer and basal cell carcinoma risk [0.92 (0.88-0.96), P <0.001, 0.92 (0.85-0.99), P =0.029, respectively], and with increased colorectal cancer risk [1.12 (1.07-1.18), P <0.001]. In addition, there was no suggestive evidence to support the association of GLP1RA with ovarian cancer [0.99 (0.90-1.09), P =0.827], lung cancer [1.01 (0.93-1.10), P =0760], and thyroid cancer [0.83 (0.63-1.10), P =0.187]. Our findings were consistent with the meta-analysis. Finally, 80 RCTs were included in the systematic review, with a low incidence of different kinds of cancer.

CONCLUSIONS

Our study suggests that GLP1RA may decrease the risk of breast cancer and basal cell carcinoma, but increase the risk of colorectal cancer. However, according to the systematic review of RCTs, the incidence of cancer in patients treated with GLP1RA is low. Larger sample sizes of RCTs with long-term follow-up are necessary to establish the incidence of cancers and evaluate the risk-benefit ratios.

Causal association of dietary factors with five common cancers: univariate and multivariate Mendelian randomization studies

Background

Daily dietary habits are closely related to human health, and long-term unhealthy dietary intake, such as excessive consumption of alcohol and pickled foods, may promote the development of cancers. However, comprehensive research on the causal relationship between dietary habits and cancer is lacking. Therefore, this study aimed to reveal the potential causal link between dietary risk factors and the prognosis of cancer-related to genetic susceptibility.

Methods

GWAS (Genome-Wide Association Studies) summary data on dietary habits and five common types of cancer and their pathological subtypes were obtained from the UK Biobank and various cancer association consortia. A univariable two-sample Mendelian randomization (UVMR) and FDR correction analysis was conducted to explore the causal relationships between 45 dietary habits and five common types of cancer and their histopathological subtypes. In addition, multivariable Mendelian randomization analysis (MVMR) was performed to adjust for traditional risk factors for dietary habits, and the direct or indirect effects of diet on cancer were evaluated. Finally, the prognostic impact of selected instrumental variables on cancer was analyzed using an online data platform.

Results

In the UVMR analysis, four dietary habits were identified as risk factors for cancer, while five dietary habits were identified as protective factors. Among the latter, one dietary habit showed a significant association with cancer even after FDR correction, indicating a potential causal relationship. The MVMR analysis revealed that weekly beer and cider intake, may act as an independent risk factor for cancer development. Other causal associations between dietary habits and cancer risk may be mediated by intermediate factors. In the prognostic analysis, the SNPs (Single Nucleotide Polymorphisms) of average weekly beer and cider intake were set as independent risk factors and were found to significantly impact overall survival (OS) and cancer-specific survival (CSS) in lung cancer.

Conclusion

This causal relationship study supports the notion that adjusting daily dietary habits and specific dietary interventions may decrease the risk of cancer.

Using Genetics to Investigate Relationships between Phenotypes: Application to Endometrial Cancer

Genome-wide association studies (GWAS) have accelerated the exploration of genotype-phenotype associations, facilitating the discovery of replicable genetic markers associated with specific traits or complex diseases. This narrative review explores the statistical methodologies developed using GWAS data to investigate relationships between various phenotypes, focusing on endometrial cancer, the most prevalent gynecological malignancy in developed nations. Advancements in analytical techniques such as genetic correlation, colocalization, cross-trait locus identification, and causal inference analyses have enabled deeper exploration of associations between different phenotypes, enhancing statistical power to uncover novel genetic risk regions. These analyses have unveiled shared genetic associations between endometrial cancer and many phenotypes, enabling identification of novel endometrial cancer risk loci and furthering our understanding of risk factors and biological processes underlying this disease. The current status of research in endometrial cancer is robust; however, this review demonstrates that further opportunities exist in statistical genetics that hold promise for advancing the understanding of endometrial cancer and other complex diseases.

Insights into inflammation and implications for the pathogenesis and long-term outcomes of endometrial cancer: genome-wide surveys and a clinical cohort study

BACKGROUND

Despite evidence showing a connection between inflammation and endometrial cancer (EC) risk, the surveys on genetic correlation and cohort studies investigating the impact on long-term outcomes have yet to be refined. We aimed to address the impact of inflammation factors on the pathogenesis, progression and consequences of EC.

METHODS

For the genetic correlation analyses, a two-sample of Mendelian randomization (MR) study was applied to investigate inflammation-related single-nucleotide polymorphisms involved with endometrial cancer from GWAS databases. The observational retrospective study included consecutive patients diagnosed with EC (stage I to IV) with surgeries between January 2010 and October 2020 at the Cancer Hospital of Shantou University Medical College.

RESULTS

The 2-sample MR surveys indicated no causal relationship between inflammatory cytokines and endometrial cancer. 780 cases (median age, 55.0 years ) diagnosed with EC were included in the cohort and followed up for an average of 6.8 years. Increased inflammatory parameters at baseline were associated with a higher FIGO stage and invasive EC risk (odds ratios [OR] 1.01 to 4.20). Multivariate-cox regression suggested that multiple inflammatory indicators were significantly associated with overall survival (OS) and progression-free survival (PFS) (P < 0.05). Nomogram models based on inflammatory risk and clinical factors were developed for OS and PFS with C-index of 0.811 and 0.789, respectively. LASSO regression for the validation supported the predictive efficacy of inflammatory and clinical factors on the long-term outcomes of EC.

CONCLUSIONS

Despite the fact that the genetic surveys did not show a detrimental impact of inflammatory cytokines on the endometrial cancer risk, our cohort study suggested that inflammatory level was associated with the progression and long-term outcomes of EC. This evidence may contribute to new strategies targeted at decreasing inflammation levels during EC therapy.

Sleep, physical activity, and sedentary behaviors in relation to overall cancer and site-specific cancer risk: A prospective cohort study

Large prospective studies are required to better elucidate the associations of physical activity, sedentary behaviors (SBs), and sleep with overall cancer and site-specific cancer risk, accounting for the interactions with genetic predisposition. The study included 360,271 individuals in UK Biobank. After a median follow-up of 12.52 years, we found higher total physical activity (TPA) level and higher sleep scores were related to reduced risk of cancer while higher SB level showed a positive association with cancer. Compared with high TPA-healthy sleep group and low SB-healthy sleep group, low TPA-poor sleep group and high SB-poor sleep group had the highest risk for overall cancer, breast cancer, and lung cancer. Adherence to a more active exercise pattern was associated with a lower risk of cancer irrespective of genetic risk. Our study suggests that improving the quality of sleep and developing physical activity habits might yield benefits in mitigating the cancer risk.

GGTLC1 knockdown inhibits the progression of endometrial cancer by regulating the TGF-β/Smad signaling pathway

Purpose

Endometrial cancer (EC) poses a serious risk to females worldwide; thus, a deep understanding of EC is urgently required. The role and mechanisms of gamma-glutamyltransferase light chain 1 (GGTLC1) in EC remain obscure. This study aims to elucidate the function and mechanisms underlying GGTLC1's involvement in EC.

Methods

Bioinformatic tools and databases were used to analyze GGTLC1 and its associated gene expression in EC tissues. Functional enrichment explorations and immune infiltration analyses were conducted, together with investigation into the methylation status of GGTLC1. Western blotting and Quantitative real-time PCR quantified expression levels. Additional experimental methodologies elucidated the role of GGTLC1 in EC progression. Transcriptome sequencing identified potential regulatory pathways for GGTLC1, and tumor growth was evaluated in vivo using HEC-1A cells in nude mice.

Results

GGTLC1 was upregulated and negatively correlated with immune cell infiltration and DNA methylation in EC. Cell migration and proliferation were reduced following GGTLC1 knockdown, together with arrest at the G0/G1 phase and an upsurge in apoptosis. Compared to the knockdown group, TGF-β/Smad signaling pathway was up-regulated in the negative control group of EC cells by transcriptome analysis. The levels of TGF-β, pSmad2, and pSmad3 followed the same decreasing trend, whereas Smad3 and Smad2 protein levels remained unchanged.

Conclusion

Knockdown of GGTLC1 attenuates EC development through the TGF-β/Smad pathway, positioning GGTLC1 as a promising target for EC treatment.