Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions

Nonadditive Effects of Common Genetic Variants Have a Negligent Contribution to Cancer Heritability

BACKGROUND

Contribution of dominance effects to cancer heritability is unknown. We leveraged existing genome-wide association data for seven cancers to estimate the contribution of dominance effects to the heritability of individual cancer types.

METHODS

We estimated the proportion of phenotypic variation caused by dominance genetic effects using genome-wide association data for seven cancers (breast, colorectal, lung, melanoma, nonmelanoma skin, ovarian, and prostate) in a total of 166,772 cases and 284,824 controls.

RESULTS

We observed no evidence of a meaningful contribution of dominance effects to cancer heritability. By contrast, additive effects ranged between 0.11 and 0.34.

CONCLUSIONS

In line with studies of other human traits, the dominance effects of common genetic variants play a minimal role in cancer etiology.

IMPACT

These results support the assumption of an additive inheritance model when conducting cancer association studies with common genetic variants.

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.

HPV16 Phylogenetic Variants in Anogenital and Head and Neck Cancers: State of the Art and Perspectives

HPV16 is responsible for approximately 60% and 90% of global HPV-induced cervical and oropharyngeal cancers, respectively. HPV16 intratype variants have been identified by HPV genome sequencing and classified into four phylogenetic lineages (A-D). Our understanding of HPV16 variants mostly derives from epidemiological studies on cervical cancer (CC) in which HPV16 B, C, and D lineages (previously named "non-European" variants) were mainly associated with high-grade cervical lesions and cancer. Although a predominance of HPV16 lineage A (previously named "European variants") has been observed in head and neck squamous cell carcinoma (HNSCC), epidemiological and in vitro biological studies are still limited for this tumor site. Next Generation Sequencing (NGS) of the entire HPV genome has deepened our knowledge of the prevalence and distribution of HPV variants in CC and HNSCC. Research on cervical cancer has shown that certain HPV16 sublineages, such as D2, D3, A3, and A4, are associated with an increased risk of cervical cancer, and sublineages A4, D2, and D3 are linked to a higher risk of developing adenocarcinomas. Additionally, lineage C and sublineages D2 or D3 of HPV16 show an elevated risk of developing premalignant cervical lesions. However, it is still crucial to conduct large-scale studies on HPV16 variants in different HPV-related tumor sites to deeply evaluate their association with disease development and outcomes. This review discusses the current knowledge and updates on HPV16 phylogenetic variants distribution in HPV-driven anogenital and head and neck cancers.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

Backgrounds

Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population.

Methods

A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes.

Results

Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable.

Conclusion

We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Mendelian randomization analysis of atopic dermatitis and esophageal cancer in East Asian and European populations

Background

Emerging observational studies showed an association between atopic dermatitis (AD) and gastrointestinal cancers. However, it remains unclear whether this association is causal, particularly in the case of cancers like esophageal cancer, which exhibit ancestral genetic traits.

Methods

To assess the potential causal relationship between AD and esophageal cancer across diverse ancestral backgrounds, we conducted a 2-sample Mendelian randomization study. Independent genetic instruments for AD from the FinnGen consortium (N case = 7024 and N control = 198 740), BioBank Japan (N case = 2385 and N control = 209 651) and Early Genetics and Lifecourse Epidemiology (EAGLE) eczema consortium (N case = 18 900 and N control = 84 166, without the 23andMe study) were used to investigate the association with esophageal cancer in the UK Biobank study (N case = 740 and N control = 372 016) and BioBank Japan esophageal cancer sample (N case = 1300 and N control = 197 045).

Results

When esophageal cancer extracted from East Asian ancestry was used as a outcome factor, AD data extracted from BioBank Japan (OR = 0.90, 95% CI: 0.83-0.98), FinnGen consortium (OR = 0.86, 95% CI: 0.77-0.96), and EAGLE consortium (OR = 0.92, 95% CI: 0.81-1.06) were negatively associated with esophageal cancer susceptibility. However, AD as a whole did not show an association with esophageal cancer from European ancestry.

Conclusion

This study provides support for a causal relationship between AD and esophageal cancer in East Asian populations but not between AD and esophageal cancer from European ancestry. The specific associations between esophageal cancer and AD appear to exhibit significant disparities between the East Asian and European regions.

Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants

The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.