A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

Precision proteogenomics reveals pan-cancer impact of germline variants

We investigate the impact of germline variants on cancer patients' proteomes, encompassing 1,064 individuals across 10 cancer types. We introduced an approach, "precision peptidomics," mapping 337,469 coding germline variants onto peptides from patients' mass spectrometry data, revealing their potential impact on post-translational modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases. We identified rare pathogenic and common germline variants in cancer genes potentially affecting proteomic features, including variants altering protein abundance and structure and variants in kinases (ERBB2 and MAP2K2) impacting phosphorylation. Precision peptidome analysis predicted destabilizing events in signal-regulatory protein alpha (SIRPA) and glial fibrillary acid protein (GFAP), relevant to immunomodulation and glioblastoma diagnostics, respectively. Genome-wide association studies identified quantitative trait loci for gene expression and protein levels, spanning millions of SNPs and thousands of proteins. Polygenic risk scores correlated with distal effects from risk variants. Our findings emphasize the contribution of germline genetics to cancer heterogeneity and high-throughput precision peptidomics.

Novel Parkinson's Disease Genetic Risk Factors Within and Across European Populations

Introduction

We conducted a meta-analysis of Parkinson's disease genome-wide association study summary statistics, stratified by source (clinically-recruited case-control cohorts versus population biobanks) and by general European versus European isolate ancestries. This study included 63,555 cases, 17,700 proxy cases with a family history of Parkinson's disease, and 1,746,386 controls, making it the largest investigation of Parkinson's disease genetic risk to date.

Methods

Meta-analyses were performed using standard fixed and random effect models for the European sub-populations, the case-control studies, and the population biobanks separately. Finally, all of the European ancestries for all study types as well as proxy cases were combined in our final cross-European meta-analysis. We estimated heritable risk across ancestry groups, investigated tissue and cell-type enrichment, and prioritized risk genes using public data to facilitate functional follow-up efforts.

Results

The final combined cross-European meta-analysis identified 134 risk loci (59 novel), with a total of 157 independent signals, significantly expanding our understanding of Parkinson's disease risk. Multi-omic data integration revealed that expression of the nominated risk genes are highly enriched in brain tissues, particularly in neuronal and astrocyte cell types. Additionally, we prioritized 33 high-confidence genes across these 134 loci for future follow-up studies.

Conclusions

By integrating diverse European populations and leveraging harmonized data from the Global Parkinson's Genetics Program (GP2), we reveal new insight into the genetic architecture of Parkinson's disease. We identified a total of 134 risk loci, expanding the number of known loci associated with PD by approximately 24%. We also provided an initial layer of biological context to these results through follow-up analyses in an effort to facilitate follow-up studies and precision medicine efforts with the goal of advancing Parkinson's disease research.

Carotenoids as modulators of the PI3K/Akt/mTOR pathway: innovative strategies in cancer therapy

Cancer progression is primarily driven by the uncontrolled activation of cellular signaling pathways, with the PI3K/Akt/mTOR (PAMT) pathway playing a central role. This pathway significantly contributes to the proliferation and survival of cancer cells, and its hyperactivity is a major challenge in managing several types of malignancies. This article delves into the promising potential of carotenoids, natural pigments found in abundance in fruits and vegetables, as a novel therapeutic strategy for cancer treatment. By specifically targeting and inhibiting the PAMT pathway, carotenoids may effectively disrupt the growth and survival of cancer cells. The article examines the complex mechanisms underlying these interactions and highlights the obstacles faced in cancer treatment. It proposes a compelling approach to developing therapies that leverage natural products to target this critical pathway, offering a fresh perspective on cancer treatment. Further research is essential to enhance the therapeutic efficacy of these compounds.

Lower FGFR2 mRNA Expression and Higher Levels of FGFR2 IIIc in HER2-Positive Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) has been associated with breast cancer. We performed in silico analyses to investigate the FGFR2 mRNA expression and splice variants associated with breast cancer subtypes. Online databases, including cBioPortal and TCGA SpliceSeq, were used to examine the association between the FGFR2 expression and splice variants with breast cancer subtypes. A higher FGFR2 mRNA was significantly associated with luminal, oestrogen receptor (ER)-positive breast cancers, and invasive lobular carcinomas, whereas a lower FGFR2 was associated with human epidermal growth factor receptor 2 (HER2)-positive breast cancer and invasive ductal carcinomas. The epithelial alternatively spliced FGFR2 IIIb isoform was significantly enriched in ER+ breast cancer, while the mesenchymal FGFR2 IIIc isoform was significantly prevalent in HER2+ cancer. Increased levels of FGFR2 and IIIb splice isoforms are associated with less aggressive breast cancer phenotypes, while decreased levels of FGFR2 and increased IIIc splice isoform are associated with more aggressive phenotypes.

Mammary adipocytes promote breast tumor cell invasion and angiogenesis in the context of menopause and obesity

The mechanism(s) underlying obesity-related postmenopausal (PM) breast cancer (BC) are not clearly understood. We hypothesized that the increased local presence of 'obese' mammary adipocytes within the BC microenvironment promotes the acquisition of an invasive and angiogenic BC cell phenotype and accelerates tumor proliferation and progression. BC cells, treated with primary mammary adipocyte secretome from premenopausal (Pre-M) and PM obese women (ObAdCM; obese adipocyte conditioned-media) upregulated the expression of several pro-tumorigenic factors including VEGF, lipocalin-2 and IL-6. Both Pre-M and PM ObAdCM stimulated endothelial cell recruitment and proliferation and significantly stimulated BC cell proliferation, migration and invasion. IL-6 and LCN2 induced STAT3/Akt signaling in BC cells and STAT3 inhibition abrogated the ObAdCM-stimulated BC cell proliferation and migration. Expression of proangiogenic regulators including VEGF, NRP1, NRP2, IL8RB, TGFβ2, and TSP-1 were found to be differentially regulated in mammary adipocytes from obese PM women. Comparative RNAseq indicated an upregulation of PI3K/Akt signaling, ECM-receptor interactions and lipid/fatty acid metabolism in PM versus Pre-M mammary adipocytes. Our results demonstrate that irrespective of menopausal status, cross-talk between obese mammary adipocytes and BC cells promotes tumor aggressiveness and suggest that targeting the LCN2/IL-6/STAT3 signaling axis may be a useful strategy in obesity-driven breast tumorigenesis.

Receptor tyrosine kinases in breast cancer treatment: unraveling the potential

Breast cancer is a multifactorial disease driven by acquired genetic and epigenetic changes that lead to aberrant regulation of cellular signaling pathways. Receptor tyrosine kinases (RTKs), a class of critical receptors, are involved in the initiation and progression of breast cancer. RTKs are cell surface receptors with unique structures and biological characteristics, which respond to environmental signals by initiating signaling cascades such as the mitogen-activated protein kinase (MAPK) pathway, Janus kinase (JAK)/signal transducer, activator of transcription (STAT) pathway, and phosphoinositide 3-kinase (PI3K)/AKT pathway. The critical role of RTKs makes them suitable targets for breast cancer treatment. Targeted therapies against RTKs have been developed in recent years, evaluated in clinical trials, and approved for several cancer types, including breast cancer. However, breast cancer displays molecular heterogeneity and exhibits different therapeutic responses to various drug types, leading to limited effectiveness of targeted therapy against RTKs. In this review, we summarize the structural and functional characteristics of selected RTKs and discuss the mechanisms and current status of drug therapy involving different protein tyrosine kinases in breast cancer progression.

Identification of Sweetness Preference-Related Single-Nucleotide Polymorphisms for Polygenic Risk Scores Associated with Obesity

Our study aimed to identify sweetness preference-associated single-nucleotide polymorphisms (SNPs), characterize the related genetic loci, and develop SNP-based polygenic risk scores (PRS) to analyze their associations with obesity. For genotyping, we utilized a pooled genome-wide association study (GWAS) dataset of 18,499 females and 10,878 males. We conducted genome-wide association analyses, functional annotation, and employed the weighted method to calculate the levels of PRS from 677 sweetness preference-related SNPs. We used Cox proportional hazards modeling with time-varying covariates to estimate age-adjusted and multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) for obesity incidence. We also tested the correlation between PRS and environmental factors, including smoking and dietary components, on obesity. Our results showed that in males, the TT genotype of rs4861982 significantly increased obesity risk compared to the GG genotype in the Health Professionals Follow-up Study (HPFS) cohort (HR = 1.565; 95% CI, 1.122-2.184; p = 0.008) and in the pooled analysis (HR = 1.259; 95% CI, 1.030-1.540; p = 0.025). Protein tyrosine phosphatase receptor type O (PTPRO) was identified as strongly associated with sweetness preference, indicating a positive correlation between sweetness preference and obesity risk. Moreover, each 10 pack-year increment in smoking was significantly associated with an increased risk of obesity in the HPFS cohort (HR = 1.024; 95% CI, 1.000-1.048) in males but not in females. In conclusion, significant associations between rs4861982, sweetness preference, and obesity were identified, particularly among males, where environmental factors like smoking are also correlated with obesity risk.

Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

Changes in mouse epidermal DNA methylation during development of squamous cell carcinoma in response to UVR

Squamous cell carcinoma (SCC) is a common skin cancer, often caused by exposure to ultraviolet radiation (UVR). Recent studies have shown that changes in DNA methylation play a crucial role in the development of cancers. However, methylation patterns of SCC are not well characterised. Identifying biomarkers for the risk of developing SCC could be helpful for early detection and diagnosis and can potentially improve treatment and prevention strategies. This study aimed to investigate methylation changes in the epidermis of mice exposed to UVR for 24 weeks. We examined the DNA methylation levels of 260 199 CpGs using the Illumina Infinium Mouse Methylation BeadChip and studied the epidermis of UVR-exposed and unexposed mice every 4 weeks for 24 weeks (n = 39). We identified CpGs with large differences in methylation levels (β-values) between UVR-exposed and unexposed mice. We also observed differences in the epigenetic age of these mice. We identified CpGs in Rev, Ipmk, Rad51b, Fgfr2, Fgfr3 and Ctnnb1 that may serve as potential biomarkers for SCC risk and could be helpful for the early detection and prevention of SCC. Further investigations are necessary to determine the biological functions and clinical significance of these CpGs.

The mutation of NSUN5 R295C promotes preeclampsia by impairing decidualization through downregulating IL-11Rα

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder that severely impairs maternal and fetal health. However, its pathogenesis remains elusive. NOP2/Sun5 (NSUN5) is an RNA methyltransferase. This study discovered a significant correlation between rs77133388 of NSUN5 and PE in a cohort of 868 severe PE patients and 982 healthy controls. To further explore this association, the researchers generated single-base mutant mice (NSUN5 R295C) at rs77133388. The pregnant NSUN5 R295C mice exhibited PE symptoms. Additionally, compared to the controls, the decidual area of the placenta was significantly reduced in NSUN5 R295C mice, and their decidualization was impaired with a significantly decrease in polyploid cell numbers after artificially induced decidualization. The study also found a decrease in phosphorylated JAK2, STAT3, and IL-11Rα, Cyclin D3 expression in NSUN5 R295C mice. Overall, these findings suggest that NSUN5 mutation potentially alters decidualization through the IL-11Rα/JAK2/STAT3/Cyclin D3 pathway, ultimately impairing placental development and contributing to PE occurrence.

FGFR2 genetic variants in women with breast cancer

Black African populations are more genetically diverse than others, but genetic variants have been studied primarily in European populations. The present study examined the association of four single nucleotide polymorphisms (SNPs) of the fibroblast growth factor receptor 2, associated with breast cancer in non‑African populations, with breast cancer in Black, southern African women. Genomic DNA was extracted from whole blood samples of 1,001 patients with breast cancer and 1,006 controls (without breast cancer), and the rs2981582, rs35054928, rs2981578, and rs11200014 polymorphisms were analyzed using allele‑specific Kompetitive allele‑specific PCR™, and the χ2 or Fisher's exact tests were used to compare the genotype frequencies. There was no association between those SNPs and breast cancer in the studied cohort, although an association was identified between the C/C homozygote genotype for rs2981578 and invasive lobular carcinoma. These results show that genetic biomarkers of breast cancer risk in European populations are not necessarily associated with risk in sub‑Saharan African populations. African populations are more heterogenous than other populations, and the information from this population can help focus genetic risks of cancer in this understudied population.

Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis

Complex diseases are generally caused by disorders of biological networks and/or mutations in multiple genes. Comparisons of network topologies between different disease states can highlight key factors in their dynamic processes. Here, we propose a differential modular analysis approach that integrates protein-protein interactions with gene expression profiles for modular analysis, and introduces inter-modular edges and date hubs to identify the "core network module" that quantifies the significant phenotypic variation. Then, based on this core network module, key factors, including functional protein-protein interactions, pathways, and driver mutations, are predicted by the topological-functional connection score and structural modeling. We applied this approach to analyze the lymph node metastasis (LNM) process in breast cancer. The functional enrichment analysis showed that both inter-modular edges and date hubs play important roles in cancer metastasis and invasion, and in metastasis hallmarks. The structural mutation analysis suggested that the LNM of breast cancer may be the outcome of the dysfunction of rearranged during transfection (RET) proto-oncogene-related interactions and the non-canonical calcium signaling pathway via an allosteric mutation of RET. We believe that the proposed method can provide new insights into disease progression such as cancer metastasis.

Single nucleotide polymorphisms associated with female breast cancer susceptibility in Chinese population

Breast cancer is a complex disease influenced by both external and internal factors, among which genetic factors play a critical role. Single-nucleotide polymorphisms (SNPs) are major contributors to the heritability of breast cancer, and their frequencies vary across ethnic groups. In this study, we aimed to investigate the association between 34 SNPs identified in previous genome-wide association studies (GWAS) and overall breast cancer risk, as well as breast cancer subtypes, in the Chinese female population. To accomplish this, we conducted an extensive association analysis using the high-throughput Sequenom MassARRAY® platform in a case-control study comprising 1848 breast cancer patients and 709 healthy controls. Our analysis, which utilized the SNPassoc package in R based on chi-squared (χ2) test and genetic model analysis, identified significant associations between breast cancer risk and SNP rs12493607 (TGFBR2, risk allele C, OR = 1.28 [1.11-1.47], P = 0.0005), as well as a less conservatively significant association with rs4784227 (CASC16, risk allele T, OR = 1.24 [1.08-1.42], P = 0.0017) and rs2046210 (ESR1, risk allele A, OR = 1.50 [1.16-1.95], P = 0.0016). Furthermore, our stratified analyses revealed that rs12493607 was significantly associated with invasive carcinoma, estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, HER2-negative, and young (aged younger than 45) breast cancer. SNP rs4784227 and rs3803662 (CASC16) were associated with invasive carcinoma and ER-positive breast cancer, while rs2046210 was linked to ductal carcinoma in situ, ER-negative, PR-negative, HER2-positive, and elder (aged more than 45) breast cancers. SNPs rs10484919 (ESR1) and rs1038304 (CCDC170) showed links to HER2-positive breast cancer, and rs616488 (PEX14) with premenopausal breast cancer. In summary, our study shed light on the relationship between SNPs and breast cancer susceptibility within a vast Chinese cohort, supporting the development of polygenetic risk scores for the Chinese population. These findings provide valuable insights into the genetic basis of breast cancer and have important implications for risk prediction, early detection, and personalized treatment of this disease.

Rare variant association on unrelated individuals in case-control studies using aggregation tests: existing methods and current limitations

Over the past years, progress made in next-generation sequencing technologies and bioinformatics have sparked a surge in association studies. Especially, genome-wide association studies (GWASs) have demonstrated their effectiveness in identifying disease associations with common genetic variants. Yet, rare variants can contribute to additional disease risk or trait heterogeneity. Because GWASs are underpowered for detecting association with such variants, numerous statistical methods have been recently proposed. Aggregation tests collapse multiple rare variants within a genetic region (e.g. gene, gene set, genomic loci) to test for association. An increasing number of studies using such methods successfully identified trait-associated rare variants and led to a better understanding of the underlying disease mechanism. In this review, we compare existing aggregation tests, their statistical features and scope of application, splitting them into the five classical classes: burden, adaptive burden, variance-component, omnibus and other. Finally, we describe some limitations of current aggregation tests, highlighting potential direction for further investigations.

miRNA-381-3p Functions as a Tumor Suppressor to Inhibit Gastric Cancer by Targeting Fibroblast Growth Factor Receptor-2

Objectives: MicroRNAs possess essential effects on gastric cancer (GC), whereas the underlying mechanisms have not been fully uncovered. The present work focused on investigating the role of miR-381-3p in GC cellular processes and the possible mechanisms. Materials and Methods: miR-381-3p levels within GC tissues and cells were measured through quantitative real-time polymerase chain reaction (qRT-PCR). This study measured cell proliferation, apoptosis, and metastasis through EdU, colony formation, flow cytometry, and Transwell assays separately. TargetScan was adopted to predict the miR-381-3p targets, whereas luciferase reporter assay was adopted for confirmation. Results: miR-381-3p levels were decreased, whereas fibroblast growth factor receptor-2 (FGFR2) expression was increased in GC. miR-381-3p upregulation inhibited proliferation, migration, and invasion and it promoted the apoptosis of GC cells. Further, FGFR2 overexpression partly reversed the miR-381-3p-mediated impacts on GC cellular processes. Conclusions: This study provides an experimental basis, suggesting the potential of using miR-381-3p as the novel marker for GC. Clinical Trial Registration number: 2020-05.

Comparisons of clinical characteristics, prognosis, epidemiological factors, and genetic susceptibility between HER2-low and HER2-zero breast cancer among Chinese females

BACKGROUND

Traditional human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) is recommended to be divided into HER2-low and HER2-zero subtypes due to different prognosis. However, few studies investigated their differences in clinical characteristics and prognosis among Chinese HER2-negative BC and their stratified differences by hormone receptor (HR), while fewer studies investigated their differences in epidemiological factors and genetic susceptibility.

METHODS

A total of 11,911 HER2-negative BC were included to compare the clinical characteristics and prognosis between HER2-zero and HER2-low BC, and 4227 of the 11,911 HER2-negative BC were further compared to 5653 controls to investigate subtype-specific epidemiological factors and single nucleotide polymorphisms(SNPs).

RESULTS

Overall, 64.2% of HER2-negative BC were HER2-low BC, and the stratified proportions of HER2-low BC were 61.9% and 75.2% for HR-positive and HR-negative BC, respectively. Compared to HER2-zero BC, HER2-low BC among HR-positive BC showed younger age at diagnosis, later stage, poorer differentiation, and higher Ki-67, while elder age at diagnosis and lower mortality were observed for HER2-low BC among HR-negative BC (all p values <0.05). Compared to healthy controls, both HER2-low and HER2-zero BC are associated with similar epidemiological factors and SNPs. However, stronger interaction between epidemiological factors and polygenic risk scores were observed for HER2-zero BC than HER2-low BC among either HR-positive [odds ratios: 10.71 (7.55-15.17) and 8.84 (6.19-12.62) for the highest risk group compared to the lowest risk group] or HR-negative BC [7.00 (3.14-15.63) and 5.70 (3.26-9.98)].

CONCLUSIONS

HER2-low BC should deserve more attention than HER2-zero BC, especially in HR-negative BC, due to larger proportion, less clinical heterogeneity, better prognosis, and less susceptibility to risk factors.

Polygenic risk scores for prediction of breast cancer in Korean women

BACKGROUND

Polygenic risk scores (PRSs) for breast cancer, developed using European and Asian genome-wide association studies (GWAS), have been shown to have good discrimination in Asian women. However, prospective calibration of absolute risk prediction models, based on a PRS or PRS combined with lifestyle, clinical and environmental factors, in Asian women is limited.

METHODS

We consider several PRSs trained using European and/or Asian GWAS. For each PRS, we evaluate the discrimination and calibration of three absolute risk models among 41 031 women from the Korean Cancer Prevention Study (KCPS)-II Biobank: (i) a model using incidence, mortality and risk factor distributions (reference inputs) among US women and European relative risks; (ii) a recalibrated model, using Korean reference but European relative risks; and (iii) a fully Korean-based model using Korean reference and relative risk estimates from KCPS.

RESULTS

All Asian and European PRS improved discrimination over lifestyle, clinical and environmental (Qx) factors in Korean women. US-based absolute risk models overestimated the risks for women aged ≥50 years, and this overestimation was larger for models that only included PRS (expected-to-observed ratio E/O = 1.2 for women <50, E/O = 2.7 for women ≥50). Recalibrated and Korean-based risk models had better calibration in the large, although the risk in the highest decile was consistently overestimated. Absolute risk projections suggest that risk-reducing lifestyle changes would lead to larger absolute risk reductions among women at higher PRS.

CONCLUSIONS

Absolute risk models incorporating PRS trained in European and Asian GWAS and population-appropriate average age-specific incidences may be useful for risk-stratified interventions in Korean women.

Genome-wide association testing in malaria studies in the presence of overdominance

BACKGROUND

In human genetics, heterozygote advantage (heterosis) has been detected in studies that focused on specific genes but not in genome-wide association studies (GWAS). For example, heterosis is believed to confer resistance to certain strains of malaria in patients heterozygous for the sickle-cell gene, haemoglobin S (HbS). Yet the power of allelic tests can be substantially diminished by heterosis. Since GWAS (and haplotype-associations) also utilize allelic tests, it is unclear to what degree GWAS could underachieve because heterosis is ignored.

METHODS

In this study, a two-step approach to genetic association testing in malaria studies in a GWAS setting that may enhance the power of the tests was proposed, by identifying the underlying genetic model first before applying the association tests. Generalized linear models for dominant, recessive, additive, and heterotic effects were fitted and model selection was performed. This was achieved via tests of significance using the MAX and allelic tests, noting the minimum p-values across all the models and the proportion of tests that a given genetic model was deemed the best. An example dataset, based on 17 SNPs, from a robust genetic association study and simulated genotype datasets, were used to illustrate the method. Case-control genotype data on malaria from Kenya and Gambia were used for validation.

RESULTS AND CONCLUSION

Results showed that the allelic test returned some false negatives under the heterosis model, suggesting reduced power in testing genetic association. Disparities were observed for some chromosomes in the Kenyan and Gambian datasets, including the sex chromosomes. Thus, GWAS and haplotype associations should be treated with caution, unless the underlying genetic model had been determined.

The FGF/FGFR signalling mediated anti-cancer drug resistance and therapeutic intervention

Fibroblast Growth Factor (FGF) ligands and their receptors are crucial factors driving chemoresistance in several malignancies, challenging the efficacy of currently available anti-cancer drugs. The Fibroblast growth factor/receptor (FGF/FGFR) signalling malfunctions in tumor cells, resulting in a range of molecular pathways that may impact its drug effectiveness. Deregulation of cell signalling is critical since it can enhance tumor growth and metastasis. Overexpression and mutation of FGF/FGFR induce regulatory changes in the signalling pathways. Chromosomal translocation facilitating FGFR fusion production aggravates drug resistance. Apoptosis is inhibited by FGFR-activated signalling pathways, reducing multiple anti-cancer medications' destructive impacts. Angiogenesis and epithelial-mesenchymal transition (EMT) are facilitated by FGFRs-dependent signalling, which correlates with drug resistance and enhances metastasis. Further, lysosome-mediated drug sequestration is another prominent method of resistance. Inhibition of FGF/FGFR by following a plethora of therapeutic approaches such as covalent and multitarget inhibitors, ligand traps, monoclonal antibodies, recombinant FGFs, combination therapy, and targeting lysosomes and micro RNAs would be helpful. As a result, FGF/FGFR suppression treatment options are evolving nowadays. To increase positive impacts, the processes underpinning the FGF/FGFR axis' role in developing drug resistance need to be clarified, emphasizing the need for more studies to develop novel therapeutic options to address this significant problem. Communicated by Ramaswamy H. Sarma.

Evaluation of the Association between FGFR2 Gene Polymorphisms and Breast Cancer Risk in the Bangladeshi Population

Breast cancer is considered the most frequent cause of mortality from malignancy among females. Fibroblast growth factor receptor 2 (FGFR2) gene polymorphisms are highly related to the risk of breast cancer. However, no investigation has been carried out to determine the association of FGFR2 gene polymorphisms in the Bangladeshi population. Based on polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), this study was performed to evaluate the association of FGFR2 (rs1219648, rs2420946, and rs2981582) variants in 446 Bangladeshi women (226 cases and 220 controls). A significant association of the FGFR2 rs1219648 variant with breast malignancy was reported in additive model 1 (aOR = 2.87, p < 0.0001), additive model 2 (aOR = 5.62, p < 0.0001), the dominant model (aOR = 2.87, p < 0.0001), the recessive model (aOR = 4.04, p < 0.0001), and the allelic model (OR = 2.16, p < 0.0001). This investigation also explored the significant association of the rs2981582 variant with the risk of breast cancer in additive model 2 (aOR = 2. 60, p = 0.010), the recessive model (aOR = 2.47, p = 0.006), and the allelic model (OR = 1.39, p = 0.016). However, the FGFR2 rs2420946 polymorphism showed no association with breast cancer except in the overdominant model (aOR = 0.62, p = 0.048). Furthermore, GTT (p < 0.0001) haplotypes showed a correlation with breast cancer risk, and all variants showed strong linkage disequilibrium. Moreover, in silico gene expression analysis showed that the FGFR2 level was upregulated in BC tissues compared to healthy tissues. This study confirms the association of FGFR2 polymorphisms with breast cancer risk.

Exploring the overlap between alopecia areata and major depressive disorder: Epidemiological and genetic perspectives

BACKGROUND

Research suggests that Alopecia areata (AA) and Major Depressive Disorder (MDD) show substantial comorbidity. To date, no study has investigated the hypothesis that this is attributable to shared genetic aetiology.

OBJECTIVES

To investigate AA-MDD comorbidity on the epidemiological and molecular genetic levels.

METHODS

First, epidemiological analyses were performed using data from a cohort of adult German health insurance beneficiaries (n = 1.855 million) to determine the population-based prevalence of AA-MDD comorbidity. Second, analyses were performed to determine the prevalence of MDD in a clinical AA case-control sample with data on psychiatric phenotypes, stratifying for demographic factors to identify possible contributing factors to AA-MDD comorbidity. Third, the genetic overlap between AA and MDD was investigated using a polygenic risk score (PRS) approach and linkage disequilibrium score (LDSC) regression. For PRS, summary statistics from a large MDD GWAS meta-analysis (PGC-MD2) were used as the training sample, while a Central European AA cohort, including the above-mentioned AA patients, and an independent replication US-AA cohort were used as target samples. LDSC was performed using summary statistics of PGC-MD2 and the largest AA meta-analysis to date.

RESULTS

High levels of AA-MDD comorbidity were reported in the population-based (MDD in 24% of AA patients), and clinical samples (MDD in 44% of AA patients). MDD-PRS explained a modest proportion of variance in AA case-control status (R²  = 1%). This signal was limited to the major histocompatibility complex (MHC) region on chromosome 6. LDSC regression (excluding MHC) revealed no significant genetic correlation between AA and MDD.

CONCLUSIONS

As in previous research, AA patients showed an increased prevalence of MDD. The present analyses suggest that genetic overlap may be confined to the MHC region, which is implicated in immune function. More detailed investigation is required to refine understanding of how the MHC is involved in the development of AA and MDD comorbidity.

SB Digestor: a tailored driver gene identification tool for dissecting heterogeneous Sleeping Beauty transposon-induced tumors

Sleeping Beauty (SB) insertional mutagenesis has been widely used for genome-wide functional screening in mouse models of human cancers, however, intertumor heterogeneity can be a major obstacle in identifying common insertion sites (CISs). Although previous algorithms have been successful in defining some CISs, they also miss CISs in certain situations. A major common characteristic of these previous methods is that they do not take tumor heterogeneity into account. However, intertumoral heterogeneity directly influences the sequence read number for different tumor samples and then affects CIS identification. To precisely detect and define cancer driver genes, we developed SB Digestor, a computational algorithm that overcomes biological heterogeneity to identify more potential driver genes. Specifically, we define the relationship between the sequenced read number and putative gene number to deduce the depth cutoff for each tumor, which can reduce tumor complexity and precisely reflect intertumoral heterogeneity. Using this new tool, we re-analyzed our previously published SB-based screening dataset and identified many additional potent drivers involved in Brca1-related tumorigenesis, including Arhgap42, Tcf12, and Fgfr2. SB Digestor not only greatly enhances our ability to identify and prioritize cancer drivers from SB tumors but also substantially deepens our understanding of the intrinsic genetic basis of cancer.

Neuroimaging Genetics and Network Analysis in Alzheimer's Disease

The issue of the genetics in brain imaging phenotypes serves as a crucial link between two distinct scientific fields: neuroimaging genetics (NG). The articles included here provide solid proof that this NG link has considerable synergy. There is a suitable collection of articles that offer a wide range of viewpoints on how genetic variations affect brain structure and function. They serve as illustrations of several study approaches used in contemporary genetics and neuroscience. Genome-wide association studies and candidate-gene association are two examples of genetic techniques. Cortical gray matter structural/volumetric measures from magnetic resonance imaging (MRI) are sources of information on brain phenotypes. Together, they show how various scientific disciplines have benefited from significant technological advances, such as the single-nucleotide polymorphism array in genetics and the development of increasingly higher-resolution MRI imaging. Moreover, we discuss NG's contribution to expanding our knowledge about the heterogeneity within Alzheimer's disease as well as the benefits of different network analyses.

A systematic review and meta-analysis of the association between HOTAIR polymorphisms and susceptibility to breast cancer

INTRODUCTION

Many studies are drawing attention to the associations of HOTAIR polymorphisms and susceptibility to breast cancer, while the results remain inconsistent. We conducted a meta-analysis on the association of four common HOTAIR polymorphisms with breast cancer susceptibility.

MATERIAL AND METHODS

Eligible published articles were searched in PubMed, Embase, Cochrane library databases and Web of Science databases up to July 2019. Odds ratios with 95% confidence intervals were used to identify potential links between lncRNA HOTAIR polymorphisms and the risk of breast cancer.

RESULTS

Our results showed no significance in all genetic models of all four SNPs. Pooled analyses detected crucial links between the rs1899663 polymorphism and decreased susceptibility to breast cancer in five genetic models rather than the dominant model in the hospital-based control subgroup. For the rs920778 polymorphism, we found that it significantly decreased breast cancer risk under recessive, homozygous and heterozygous models within the west Asian subgroup and increased breast cancer risk under allele and dominant models within the East Asian subgroup. Additionally, rs920778 polymorphism decreased breast cancer risk under recessive and heterozygous models in the hospital-based control subgroup. However, no significant association was observed between the rs4759314 polymorphism and breast cancer risk in overall and stratified analyses. For rs12826786 polymorphism, it was greatly associated with decreased breast cancer risk under recessive, homozygous and heterozygous models in the hospital-based control subgroup.

CONCLUSIONS

HOTAIR rs920778, rs1899663 and rs12826786 polymorphisms may contribute to breast cancer susceptibility.

Hereditary breast cancer: syndromes, tumour pathology and molecular testing

Hereditary factors account for a significant proportion of breast cancer risk. Approximately 20% of hereditary breast cancers are attributable to pathogenic variants in the highly penetrant BRCA1 and BRCA2 genes. A proportion of the genetic risk is also explained by pathogenic variants in other breast cancer susceptibility genes, including ATM, CHEK2, PALB2, RAD51C, RAD51D and BARD1, as well as genes associated with breast cancer predisposition syndromes - TP53 (Li-Fraumeni syndrome), PTEN (Cowden syndrome), CDH1 (hereditary diffuse gastric cancer), STK11 (Peutz-Jeghers syndrome) and NF1 (neurofibromatosis type 1). Polygenic risk, the cumulative risk from carrying multiple low-penetrance breast cancer susceptibility alleles, is also a well-recognised contributor to risk. This review provides an overview of the established breast cancer susceptibility genes as well as breast cancer predisposition syndromes, highlights distinct genotype-phenotype correlations associated with germline mutation status and discusses molecular testing and therapeutic implications in the context of hereditary breast cancer.

Role of DEK in carcinogenesis, diagnosis, prognosis, and therapeutic outcome of breast cancer: An evidence-based clinical review

Breast cancer is a significantly burdening women's cancer with limited diagnostic modalities. DEK is a novel biomarker overexpressed in breast cancers, currently exhaustively researched for its diagnosis and prognosis. Search for relevant meta-analyses, cohorts, and experimental studies in the last fifteen years was done in five large scientific databases. Non-English, non-full text articles or unrelated studies were excluded. Thirteen articles discussed the potential of DEK to estimate breast cancer characteristics, treatment outcomes, and prognosis. This proto-oncogene plays a role in breast carcinogenesis, increasing tumour proliferation and invasion, preventing apoptosis, and creating an immunodeficient tumour milieu with M2 tumour-associated macrophages. DEK is also associated with worse clinicopathological features and survival in breast cancer patients. Using a Kaplan-Meier plotter data analysis, DEK expression predicts worse overall survival (HR 1.24, 95%CI: 1.01-1.52, p = 0.039), comparable to other biomarkers. DEK is a promising novel biomarker requiring further research to determine its bedside applications.

Heterozygotic Brca1 mutation initiates mouse genome instability at embryonic stage

BRCA1 mutation is the genetic predisposition in causing genome instability towards cancer. BRCA1 mutation is predominantly germline inherited at the fertilization. However, when the inherited mutation initiates genome instability in the mutation carriers remains largely elusive. We used a heterozygotic Brca1-knockout mouse as a model to investigate the issue. Through whole-genome sequencing and bioinformatics analysis, we monitored genome status across the developmental stages from embryo to adulthood in the mouse model. We observed that genome instability as reflected by structural variation, indel and copy number variation already appeared at 10.5-day embryo and progressively towards adulthood. We also observed that the genome instability was not linearly accumulated but dynamically changed along the developmental process, affecting many oncogenic genes and pathways including DNA damage repair, estrogen signaling, and oncogenesis. We further observed that many genome abnormalities in the cancer caused by Brca1 mutation were originated at embryonic stage, and Trp53 (TP53) mutation was not essential for the Brca1 mutation-caused genome instability in the non-cancer cells. Our study revealed that heterozygotic Brca1 mutation alone can cause genome instability at embryonic stage, highlighting that prevention of BRCA1 mutation-related cancer in humans may need to start earlier than currently considered.

Rat Mammary carcinoma susceptibility 3 (Mcs3) pleiotropy, socioenvironmental interaction, and comparative genomics with orthologous human 15q25.1-25.2

Genome-wide association studies of breast cancer susceptibility have revealed risk-associated genetic variants and nominated candidate genes; however, the identification of causal variants and genes is often undetermined by genome-wide association studies. Comparative genomics, utilizing Rattus norvegicus strains differing in susceptibility to mammary tumor development, is a complimentary approach to identify breast cancer susceptibility genes. Mammary carcinoma susceptibility 3 (Mcs3) is a Copenhagen (COP/NHsd) allele that confers resistance to mammary carcinomas when introgressed into a mammary carcinoma susceptible Wistar Furth (WF/NHsd) genome. Here, Mcs3 was positionally mapped to a 7.2-Mb region of RNO1 spanning rs8149408 to rs107402736 (chr1:143700228-150929594, build 6.0/rn6) using WF.COP congenic strains and 7,12-dimethylbenz(a)anthracene-induced mammary carcinogenesis. Male and female WF.COP-Mcs3 rats had significantly lower body mass compared to the Wistar Furth strain. The effect on female body mass was observed only when females were raised in the absence of males indicating a socioenvironmental interaction. Furthermore, female WF.COP-Mcs3 rats, raised in the absence of males, did not develop enhanced lobuloalveolar morphologies compared to those observed in the Wistar Furth strain. Human 15q25.1-25.2 was determined to be orthologous to rat Mcs3 (chr15:80005820-82285404 and chr15:83134545-84130720, build GRCh38/hg38). A public database search of 15q25.1-25.2 revealed genome-wide significant and nominally significant associations for body mass traits and breast cancer risk. These results support the existence of a breast cancer risk-associated allele at human 15q25.1-25.2 and warrant ultrafine mapping of rat Mcs3 and human 15q25.1-25.2 to discover novel causal genes and variants.

Cellular and neuronal mechanisms that underlie addiction - literature review

Introduction: Addictive substances act on a number of neurotransmitter systems, and the end result of this action is the activation of the reward system in the brain. The cellular and neuronal mechanisms that underlie addiction have long been searched for. One of such neurotransmitters is dopamine, a catecholamine synthesized in neurons located mainly in the midbrain.

Material and method: The available literature was reviewed on the Pubmed platform and from other sources. The analysis included original studies, reviews.

The aim of the study was to review the literature on the relationship between the DRD2 gene and the occurrence of substance addiction.

Discussion: This work presents several currently discussed biological mechanisms, especially at the molecular and genetic level, involved in the process of addiction to various psychoactive substances. They discovered the brain structures that are most at risk, as well as other neurotransmitter systems and receptor proteins through which they can exert their pathological effects. It has also been established that exposure to psychoactive substances causes significant changes in expression in over 100 genes (including genes for dopaminergic, serotonergic and signaling pathways). The DRD2 receptor (present, among others, in the nucleus accumbens) plays an important role in the reward system, in the transmission of information. The weakening of this conductivity is a significant risk factor for the onset of clinical features that are associated with reward system deficiency syndrome. The expression of the D2 receptor gene may take up to 2 isoforms: short D2S and long D2L.

Conclusions: Further research at the molecular level may result in the modification of psychotherapy and pharmacotherapy in terms of their personalization.

Genetic Obesity Variants and Risk of Conventional Adenomas and Serrated Polyps

BACKGROUND

Higher body mass index (BMI) is associated with increased risk of colorectal cancer. How genetically predicted BMI may be associated with colorectal cancer precursors is unknown.

AIMS

Our objective was to quantify the association of genetically predicted and measured BMI with risk of colorectal cancer precursors.

METHODS

We evaluated the association of genetically predicted and measured BMI with risk of conventional adenomas, serrated polyps, and synchronous polyps among 27,426 participants who had undergone at least one lower gastrointestinal endoscopy in the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study. Genetic risk score was derived from 97 BMI-related single nucleotide polymorphisms. Multivariable logistic regression evaluated each polyp subtype compared to non-polyps.

RESULTS

For conventional adenomas, the OR per 2-kg/m² increase was 1.03 (95% CI, 1.01-1.04) for measured BMI and 0.98 (95% CI, 0.88-1.10) for genetically predicted BMI; for serrated polyps, the OR was 1.06 (95% CI, 1.04-1.08) and 1.04 (95% CI, 0.90-1.20), respectively; for synchronous polyps, the OR was 1.10 (95% CI, 1.07-1.13) and 1.09 (95% CI, 0.89-1.34), respectively. Genetically predicted BMI was associated with synchronous polyps in women (OR = 1.37, 95% CI: 1.05-1.79).

CONCLUSION

Genetically predicted BMI was not associated with colorectal cancer precursor lesions. The confidence intervals were wide and encompassed those for measured BMI, indicating that null findings may be due to insufficient power.

A robust association test with multiple genetic variants and covariates

Due to the advancement of genome sequencing techniques, a great stride has been made in exome sequencing such that the association study between disease and genetic variants has become feasible. Some powerful and well-known association tests have been proposed to test the association between a group of genes and the disease of interest. However, some challenges still remain, in particular, many factors can affect the performance of testing power, e.g., the sample size, the number of causal and non-causal variants, and direction of the effect of causal variants. Recently, a powerful test, called T REM , is derived based on a random effects model. T REM has the advantages of being less sensitive to the inclusion of non-causal rare variants or low effect common variants or the presence of missing genotypes. However, the testing power of T REM can be low when a portion of causal variants has effects in opposite directions. To improve the drawback of T REM , we propose a novel test, called T ROB , which keeps the advantages of T REM and is more robust than T REM in terms of having adequate power in the case of variants with opposite directions of effect. Simulation results show that T ROB has a stable type I error rate and outperforms T REM when the proportion of risk variants decreases to a certain level and its advantage over T REM increases as the proportion decreases. Furthermore, T ROB outperforms several other competing tests in most scenarios. The proposed methodology is illustrated using the Shanghai Breast Cancer Study.

Induced mammary cancer in rat models: pathogenesis, genetics, and relevance to female breast cancer

Mammary cancer, or breast cancer in women, is a polygenic disease with a complex etiopathogenesis. While much remains elusive regarding its origin, it is well established that chemical carcinogens and endogenous estrogens contribute significantly to the initiation and progression of this disease. Rats have been useful models to study induced mammary cancer. They develop mammary tumors with comparable histopathology to humans and exhibit differences in resistance or susceptibility to mammary cancer depending on strain. While some rat strains (e.g., Sprague-Dawley) readily form mammary tumors following treatment with the chemical carcinogen, 7,12-dimethylbenz[a]-anthracene (DMBA), other strains (e.g., Copenhagen) are resistant to DMBA-induced mammary carcinogenesis. Genetic linkage in inbred strains has identified strain-specific quantitative trait loci (QTLs) affecting mammary tumors, via mechanisms that act together to promote or attenuate, and include 24 QTLs controlling the outcome of chemical induction, 10 QTLs controlling the outcome of estrogen induction, and 4 QTLs controlling the outcome of irradiation induction. Moreover, and based on shared factors affecting mammary cancer etiopathogenesis between rats and humans, including orthologous risk regions between both species, rats have served as useful models for identifying methods for breast cancer prediction and treatment. These studies in rats, combined with alternative animal models that more closely mimic advanced stages of breast cancer and/or human lifestyles, will further improve our understanding of this complex disease.

Inhibition of Fibroblast Growth Factor Receptor Attenuates Ultraviolet B-Induced Skin Carcinogenesis

Altered FGFR signaling has been shown to play a role in a number of cancers. However, the role of FGFR signaling in the development and progression of ultraviolet B-induced (UVB) induced cutaneous squamous cell carcinoma (cSCC) remains unclear. In the current study, the effect of UVB radiation on FGFR activation and its downstream signaling in mouse skin epidermis was examined. In addition, the impact of FGFR inhibition on UVB-induced signaling and skin carcinogenesis was also investigated. Exposure of mouse dorsal skin to UVB significantly increased phosphorylation of FGFRs in the epidermis as well as activation of downstream signaling pathways, including AKT/mTOR, STATs and MAPK. Topical application of the pan-FGFR inhibitor AZD4547 to mouse skin prior to exposure to UVB significantly inhibited FGFR phosphorylation as well as mTORC1, STAT3 and MAPK activation (i.e., phosphorylation). Moreover, AZD4547 pretreatment significantly inhibited UVB-induced epidermal hyperplasia and hyperproliferation and reduced infiltration of mast cells and macrophages into the dermis. AZD4547 treatment also significantly inhibited mRNA expression of inflammatory genes in the epidermis. Finally, mice treated topically with AZD4547 prior to UVB exposure showed decreased cSCC incidence and increased survival rate. Collectively, the current data supports the hypothesis that inhibition of FGFR in epidermis may provide a new strategy to prevent and/or treat UVB-induced cSCC.

Genome-wide association study identifies kallikrein 5 in type 2 inflammation-low asthma

BACKGROUND

Clinical studies of type 2 (T2) cytokine-related neutralizing antibodies in asthma have identified a substantial subset of patients with low levels of T2 inflammation who do not benefit from T2 cytokine neutralizing antibody treatment. Non type 2 mechanisms are poorly understood in asthma but represent the redefined unmet medical need.

OBJECTIVE

To gain understanding of the genetic contribution to T2-low asthma.

METHODS

We utilized an unbiased genome-wide association study (GWAS) of moderate-severe asthma patients stratified by T2 serum biomarker periostin. We also performed additional expression and biological analysis for the top genetic hit.

RESULTS

This analysis identified a novel protective SNP at chr19q13.41 which is selectively associated with T2-low asthma and establishes KLK5 as the causal gene mediating this association. Heterozygous carriers of the SNP have reduced KLK5 expression. KLK5 is secreted by human bronchial epithelial cells and elevated in asthma bronchial alveolar lavage. T2 cytokines IL-4 and IL-13 downregulate KLK5 in human bronchial epithelial cells. KLK5, dependent on its catalytic function, induces epithelial chemokine/cytokine expression. Lastly, overexpression of KLK5 in airway, or lack of an endogenous KLK5 inhibitor, SPINK5, leads to spontaneous airway neutrophilic inflammation.

CONCLUSION

Our data identifies KLK5 as the causal gene at a novel locus at chr19q13.41 associated with T2-low asthma.

2q35-rs13387042 variant and the risk of breast cancer: a case-control study

BACKGROUND

Breast Cancer is the most frequent neoplasm diagnosed among women worldwide. Genetic background and lifestyle/environment play a significant role in the disease etiology. According to Genome-wide association studies, some single-nucleotide polymorphisms such as 2q35-rs13387042-(G/A) have been introduced to be associated with breast cancer risk and features. In this study, we aimed to evaluate the association between this variant and the risk of breast cancer in a cohort of Iranian women.

METHODS

Demographics and clinical information were collected by interview and using patients' medical records, respectively. DNA was extracted from 506 blood samples, including 184 patients and 322 controls, and genotyping was performed using allele specific-PCR. SPSS v16 was used for statistical analysis.

RESULT

Statistically significant association was observed between AA genotype and disease risk in all patients [p_adj = 0.048; OR_adj = 2.13, 95% CI (1.01-4.50)] and also ER-positive breast cancers [p_adj = 0.015; OR_adj = 2.12, 95% CI (1.16-3.88)]. There was no association between rs13387042 and histopathological characteristics of the disease. Furthermore, overall survival was not statistically associated with genotype and allelic models even after adjustment for stage and receptor status (p > 0.05).

CONCLUSION

There is a statistically significant association between 2q35-rs13387042 and breast cancer risk. rs13387042-AA genotype might be a risk-conferring factor for breast cancer development in the Iranian population. However, further consideration is suggested to confirm its role in risk assessment and probable association with other genetic markers.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

The African Female Breast Cancer Epidemiology Study Protocol

Breast cancer is now the commonest cancer in most sub-Saharan African countries. Few studies of the epidemiology and genomics of breast cancer and its molecular subtypes in these countries have been done. The African Female Breast Cancer Epidemiology (AFBRECANE) study, a part of the Human Heredity and Health in Africa (H3Africa) initiative, is designed to study the genomics and epidemiology of breast cancer and its molecular subtypes in Nigerian women. We link recruitment of breast cancer cases at study sites with population-based cancer registries activities to enable ascertainment of the incidence of breast cancer and its molecular subtypes. We use centralized laboratory processing to characterize the histopathological and molecular diagnosis of breast cancer and its subtypes using multiple technologies. By combining genome-wide association study (GWAS) data from this study with that generated from 12,000 women participating in our prospective cohort study of cervical cancer, we conduct GWAS of breast cancer in an entirely indigenous African population. We test associations between dietary intakes and breast cancer and focus on vitamin D which we measure using dietary intakes, serum vitamin D, and Mendelian randomization. This paper describes the AFBRECANE project, its design, objectives and anticipated contributions to knowledge and understanding of breast cancer.

Assessment of Pediatric Cancer and Its Relationship to Environmental Contaminants: An Ecological Study in Idaho

The primary aim of this study was to determine the degree to which a multivariable principal component model based on several potentially carcinogenic metals and pesticides could explain the county-level pediatric cancer rates across Idaho. We contend that human exposure to environmental contaminants is one of the reasons for increased pediatric cancer incidence in the United States. Although several studies have been conducted to determine the relationship between environmental contaminants and carcinogenesis among children, research gaps exist in developing a meaningful association between them. For this study, pediatric cancer data was provided by the Cancer Data Registry of Idaho, concentrations of metals and metalloids in groundwater were collected from the Idaho Department of Water Resources, and pesticide use data were collected from the United States Geological Survey. Most environmental variables were significantly intercorrelated at an adjusted P-value <0.01 (97 out of 153 comparisons). Hence, a principal component analysis was employed to summarize those variables to a smaller number of components. An environmental burden index (EBI) was constructed using these principal components, which categorized the environmental burden profiles of counties into low, medium, and high. EBI was significantly associated with pediatric cancer incidence (P-value <0.05). The rate ratio of high EBI profile to low EBI profile for pediatric cancer incidence was estimated as 1.196, with lower and upper confidence intervals of 1.061 and 1.348, respectively. A model was also developed in the study using EBI to estimate the county-level pediatric cancer incidence in Idaho (Nash-Sutcliffe Efficiency = 0.97).

A Swedish Genome-Wide Haplotype Association Analysis Identifies a Novel Breast Cancer Susceptibility Locus in 8p21.2 and Characterizes Three Loci on Chromosomes 10, 11 and 16

(1) Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility. (2) Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1−25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls. (3) Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 × 10−8), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2−25 and 113 risk haplotypes of window size 50 at p < 5 × 10−8 on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68. (4) Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Fibroblast growth factor receptor signalling dysregulation and targeting in breast cancer

Fibroblast Growth Factor Receptor (FGFR) signalling plays a critical role in breast embryonal development, tissue homeostasis, tumorigenesis and metastasis. FGFR, its numerous FGF ligands and signalling partners are often dysregulated in breast cancer progression and are one of the causes of resistance to treatment in breast cancer. Furthermore, FGFR signalling on epithelial cells is affected by signals from the breast microenvironment, therefore increasing the possibility of breast developmental abnormalities or cancer progression. Increasing our understanding of the multi-layered roles of the complex family of FGFRs, their ligands FGFs and their regulatory partners may offer novel treatment strategies for breast cancer patients, as a single agent or rational co-target, which will be explored in depth in this review.

Clonal Hematopoiesis Mutations in Patients with Lung Cancer Are Associated with Lung Cancer Risk Factors

Clonal hematopoiesis (CH) is a phenomenon caused by expansion of white blood cells descended from a single hematopoietic stem cell. While CH can be associated with leukemia and some solid tumors, the relationship between CH and lung cancer remains largely unknown. To help clarify this relationship, we analyzed whole-exome sequencing (WES) data from 1,958 lung cancer cases and controls. Potential CH mutations were identified by a set of hierarchical filtering criteria in different exonic regions, and the associations between the number of CH mutations and clinical traits were investigated. Family history of lung cancer (FHLC) may exert diverse influences on the accumulation of CH mutations in different age groups. In younger subjects, FHLC was the strongest risk factor for CH mutations. Association analysis of genome-wide genetic variants identified dozens of genetic loci associated with CH mutations, including a candidate SNP rs2298110, which may promote CH by increasing expression of a potential leukemia promoter gene OTUD3. Hundreds of potentially novel CH mutations were identified, and smoking was found to potentially shape the CH mutational signature. Genetic variants and lung cancer risk factors, especially FHLC, correlated with CH. These analyses improve our understanding of the relationship between lung cancer and CH, and future experimental studies will be necessary to corroborate the uncovered correlations. SIGNIFICANCE: Analysis of whole-exome sequencing data uncovers correlations between clonal hematopoiesis and lung cancer risk factors, identifies genetic variants correlated with clonal hematopoiesis, and highlights hundreds of potential novel clonal hematopoiesis mutations.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes

BACKGROUND

Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

METHODS

Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

RESULTS

Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

CONCLUSION

This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits

Decoding the genome confers the capability to predict characteristics of the organism (phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.

Melanoma therapeutics: a literature review

Melanoma is a relentless type of skin cancer which involves myriad signaling pathways which regulate many cellular processes. This makes melanoma difficult to treat, especially when identified late. At present, therapeutics include chemotherapy, surgical resection, biochemotherapy, immunotherapy, photodynamic and targeted approaches. These interventions are usually administered as either a single-drug or in combination, based on tumor location, stage, and patients' overall health condition. However, treatment efficacy generally decreases as patients develop treatment resistance. Genetic profiling of melanocytes and the discovery of novel molecular factors involved in the pathogenesis of melanoma have helped to identify new therapeutic targets. In this literature review, we examine several newly approved therapies, and briefly describe several therapies being assessed for melanoma. The goal is to provide a comprehensive overview of recent developments and to consider future directions in the field of melanoma.

Biological Significance and Targeting of the FGFR Axis in Cancer

The pleiotropic effects of fibroblast growth factors (FGFs), the widespread expression of all seven signalling FGF receptors (FGFRs) throughout the body, and the dramatic phenotypes shown by many FGF/R knockout mice, highlight the diversity, complexity and functional importance of FGFR signalling. The FGF/R axis is critical during normal tissue development, homeostasis and repair. Therefore, it is not surprising that substantial evidence also pinpoints the involvement of aberrant FGFR signalling in disease, including tumourigenesis. FGFR aberrations in cancer include mutations, gene fusions, and amplifications as well as corrupted autocrine/paracrine loops. Indeed, many clinical trials on cancer are focusing on targeting the FGF/FGFR axis, using selective FGFR inhibitors, nonselective FGFR tyrosine kinase inhibitors, ligand traps, and monoclonal antibodies and some have already been approved for the treatment of cancer patients. The heterogeneous tumour microenvironment and complexity of FGFR signalling may be some of the factors responsible for the resistance or poor response to therapy with FGFR axis-directed therapeutic agents. In the present review we will focus on the structure and function of FGF(R)s, their common irregularities in cancer and the therapeutic value of targeting their function in cancer.

Fibroblast growth factor receptor 2 gene (FGFR2) rs2981582T/C polymorphism and susceptibility to breast cancer in Saudi women

Fibroblast growth factor receptor 2 is a protein encoded by FGFR2 gene and plays an important role in cellular growth. This study was conducted to investigate a potential association of FGFR2 rs2981582 with breast cancer. DNA was obtained from 137 Formalin-fixed, paraffin-embedded tumors and 98 normal breast tissue samples. Genotypes were carried out with PCR-RFLP. The odds ratio and 95% confidence interval (CI) were used to evaluate the power of the associations. A significant association between FGFR2 rs2981582 C allele and susceptibility to breast cancer was found (p-value < 0.0001, Odds Ratio = 2.3, %95 CI (1.5–3.0). No significant differences in FGFR2 rs2981582 genotypes and alleles distribution among breast patients with different hormonal receptor status (p > 0.05) were detected. However, a significant difference was found in genotypes and alleles distribution in ER+, PR- and HER2 between breast cancer cases and controls. This study showed an association of FGFR2 rs2981582T/C with breast cancer in Saudi women, further large study is required to validate the results.