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Genome-wide association studies identify four ER negative-specific breast cancer risk loci
Abstract
Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1 . The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4 . To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10−12 and LGR6, P = 1.4 × 10−8), 2p24.1 (P = 4.6 × 10−8) and 16q12.2 (FTO, P = 4.0 × 10−8), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
... Out of these 32 genes, 17 were previously identified in breast cancer metaanalyses which data include our 28 281 samples from the General Research Use dataset of the DRIVE Breast Cancer OncoArray Genotypes (see Table D.3). More specifically, these studies respectively used 10 707 ER-negative breast cancer cases 76 649 controls [Garcia-Closas et al.(2013)] 45 290 cases and 41 880 controls of European ancestry [Michailidou et al.(2013)], 62 623 breast cancer cases and 61 696 controls [Michailidou et al.(2015)], 122 977 cases and 105 974 controls of European ancestry together with 14 068 cases and 13 104 controls of East Asian ancestry [Michailidou et al.(2017)], and 210 088 controls (9 494 of which are BRCA1 mutation carriers) and 30 882 cases (21 468 ER-negative cases and 9 414 BRCA1 mutation carriers), all of European origin [Milne et al.(2017)]. This suggests that MuGLasso was able to rescue loci that are significant in a better-powered study (that is to say, a study with a larger number of samples). ...
... Genes found in meta-GWAS including the samples used in this work Gene symbols Evidence ASTN2 [Michailidou et al.(2017)] CCDC170 [Garcia-Closas et al.(2013), Michailidou et al.(2013), Michailidou et al.(2015)] [Michailidou et al.(2017), Milne et al.(2017)] CDYL2 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] DIRC3 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] [Milne et al.(2017)] ELL [Michailidou et al.(2013) [Michailidou et al.(2017)] KCNU1 [Michailidou et al.(2015), Michailidou et al.(2017)] NEK10 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] [Milne et al.(2017)] PAX9 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] PTHLH [Garcia-Closas et al.(2013), Michailidou et al.(2013), Michailidou et al.(2015)] [Michailidou et al.(2017), Milne et al.(2017)] SSBP4 [Michailidou et al.(2017)] TGFBR2 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] TNRC6B [Michailidou et al.(2017)] ZMIZ1 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] ZNF365 [Michailidou et al.(2017), Milne et al.(2017)] Genes found to be associated with breast cancer risk or tumor growth in the literature Gene symbols Evidence ADSL oncogenic driver in triple negative breast cancer [Zurlo et al.(2019)] CACNA1I ...
... Genes found in meta-GWAS including the samples used in this work Gene symbols Evidence ASTN2 [Michailidou et al.(2017)] CCDC170 [Garcia-Closas et al.(2013), Michailidou et al.(2013), Michailidou et al.(2015)] [Michailidou et al.(2017), Milne et al.(2017)] CDYL2 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] DIRC3 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] [Milne et al.(2017)] ELL [Michailidou et al.(2013) [Michailidou et al.(2017)] KCNU1 [Michailidou et al.(2015), Michailidou et al.(2017)] NEK10 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] [Milne et al.(2017)] PAX9 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] PTHLH [Garcia-Closas et al.(2013), Michailidou et al.(2013), Michailidou et al.(2015)] [Michailidou et al.(2017), Milne et al.(2017)] SSBP4 [Michailidou et al.(2017)] TGFBR2 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] TNRC6B [Michailidou et al.(2017)] ZMIZ1 [Michailidou et al.(2013), Michailidou et al.(2015), Michailidou et al.(2017)] ZNF365 [Michailidou et al.(2017), Milne et al.(2017)] Genes found to be associated with breast cancer risk or tumor growth in the literature Gene symbols Evidence ADSL oncogenic driver in triple negative breast cancer [Zurlo et al.(2019)] CACNA1I ...
Genome-Wide Association Studies, or GWAS, aim at finding Single Nucleotide Polymorphisms (SNPs) that are associated with a phenotype of interest. GWAS are known to suffer from the large dimensionality of the data with respect to the number of available samples. Many challenges limiting the identification of causal SNPs such as dependency between SNPs, due to linkage disequilibrium (LD), the population stratification and the low of statistical of univariate analysis. Machine learning models based on multivariate analysis contribute to advance research in GWAS. Hence, feature selection models reduce the dimensionality of data by keeping only the relevant features associated with disease. However, these methods lack of stability, that is to say, robustness to slight variations in the input dataset. This major issue can lead to false biological interpretation. Hence, we focus in this thesis on evaluating and improving the stability as it is an important indicator to trust feature selection discoveries. In this thesis, we develop two efficient novel methods (multitask group lasso and sparse multitask group lasso) for the multivariate analysis of multi-population GWAS data based on a two multitask group Lasso formulations. Each task corresponds to a subpopulation of the data, and each group to an LD-block. This formulation alleviates the curse of dimensionality, and makes it possible to identify disease LD-blocks shared across populations/tasks, as well as some that are specific to one population task. In addition, we use stability selection to increase the robustness of our approach. Finally, gap safe screening rules speed up computations enough that our method can run at a genome-wide scale. By analyzing several data including breast cancer dataset, the efficiency of the developed models was demonstrated in discovering new risk genes related to disease.
... Breast cancer genome-wide association studies (GWAS) have identified over 170 common susceptibility variants, most of them single nucleotide polymorphisms (SNPs), of which many are differentially associated with ER-positive than ER-negative disease [6][7][8]. These include 20 variants that primarily predispose to ER-negative or TN disease [7,8]. ...
... Breast cancer genome-wide association studies (GWAS) have identified over 170 common susceptibility variants, most of them single nucleotide polymorphisms (SNPs), of which many are differentially associated with ER-positive than ER-negative disease [6][7][8]. These include 20 variants that primarily predispose to ER-negative or TN disease [7,8]. However, few studies have evaluated variant associations with other tumor features, or simultaneously studied multiple, correlated tumor markers to identify source(s) of etiologic heterogeneity [7,[9][10][11][12][13]. ...
... In prior ER-negative GWAS, we identified 20 variants that predispose to ER-negative disease, of which five variants were only or most strongly associated with risk of TN disease (rs4245739, rs10069690, rs74911261, rs11374964, and rs67397200) [7,8]. We confirmed these five variants to be most strongly associated with TN disease. ...
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.
... Breast cancer genome-wide association studies (GWAS) have identified over 170 common susceptibility variants, most of them single nucleotide polymorphisms (SNPs), of which many are differentially associated with ER-positive than ER-negative disease [6][7][8]. These include 20 variants that primarily predispose to ER-negative or TN disease [7,8]. ...
... Breast cancer genome-wide association studies (GWAS) have identified over 170 common susceptibility variants, most of them single nucleotide polymorphisms (SNPs), of which many are differentially associated with ER-positive than ER-negative disease [6][7][8]. These include 20 variants that primarily predispose to ER-negative or TN disease [7,8]. However, few studies have evaluated variant associations with other tumor features, or simultaneously studied multiple, correlated tumor markers to identify source(s) of etiologic heterogeneity [7,[9][10][11][12][13]. ...
... In prior ER-negative GWAS, we identified 20 variants that predispose to ER-negative disease, of which five variants were only or most strongly associated with risk of TN disease (rs4245739, rs10069690, rs74911261, rs11374964, and rs67397200) [7,8]. We confirmed these five variants to be most strongly associated with TN disease. ...
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.
... A list of ER+ breast-cancer-associated variants were first obtained from Michailidou et al. (2013) and the NHGRI-EBI GWAS catalog ( MacArthur et al., 2017). GWAS variants associated with immunoinflammatory traits were identified using the disease category information from the Experimental Factor Ontology (EFO) database (Malone et al., 2010). ...
... In this regard, we examined the NHGRI-EBI GWAS Catalog ( MacArthur et al., 2017) and identified rs3903072 as the top breastcancer-associated variant having the highest density of proximal variants within 100 kb associated with immunoinflammatory traits (Supplementary Methods; Supplementary Figure 1; Supplementary Table 1). The SNP rs3903072 has been found to be associated with ER+ breast cancer in multiple GWAS studies ( Michailidou et al., 2013;MacArthur et al., 2017;Michailidou et al., 2017), and lies in close physical distance, but with weak genetic linkage (Supplementary Table 2), to multiple variants associated with immunoinflammatory diseases-such as rs118086960 with psoriasis (an autoimmune disease) ( Tsoi et al., 2017), rs77779142 with rosacea symptom (an inflammatory skin condition) ( Aponte et al., 2018), rs2231884 with inflammatory bowel disease (Jostins et al., 2012), and rs568617 with psoriasis and Crohn's disease (an inflammatory bowel disease) ( Ellinghaus et al., 2016) (Figure 1A; Table 1). The SNP rs3903072 shows a stronger association with breast cancer (p = 2 × 10 -12 ) than the variant rs617791 (p = 7 × 10 -6 ). ...
... eQTL and Survival Analysis Demonstrate the Tumor-Suppressive Role of CTSW To identify candidate target genes, we applied the approach of eQTL, quantifying the correlation of messenger RNA (mRNA) levels of nearby genes with the genotype status at rs3903072 (Material and Methods). Using ER+ breast tumor RNA sequencing (RNA-seq) and genotyping data from the BRCA dataset of TCGA, we identified several significant eQTL genes in cis for rs3903072, including CTSW, FIBP, MUS81, and EIF1AD (genotype p-values of a linear model adjusting for gene copy number: p= 3.52 × 10 -5 , p = 3.22 × 10 -5 , p = 1.24 × 10 -4 , p = 3.28 × 10 -3 , respectively ( Figure 1B); a complete list of eQTL genes in Supplementary Table 3), confirming the results previously reported ( Michailidou et al., 2013). Notably, CTSW was among the most significant eQTL genes; the negative correlation between CTSW expression and the number of risk alleles indicated a tumor-suppressive role of this gene (Figure 2A). ...
Genome-wide association studies (GWAS) have hitherto identified several germline variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of noncoding GWAS SNPs using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast-cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor-infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3’ end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant could regulate a gene not only in the cell of cancer origin but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.
... Breast cancer genome-wide association studies (GWAS) have identified over 170 susceptibility single nucleotide polymorphisms (SNPs), of which many are differentially associated with ER-positive than ER-negative disease [5]. These include 20 SNPs that primarily predispose to ER-negative or TN disease [6,7]. However, few studies have evaluated SNP associations with other tumor features, or simultaneously studied multiple, correlated tumor markers to identify source(s) of etiologic heterogeneity [6,[8][9][10][11][12]. ...
... In prior ER-negative GWAS we identified 20 SNPs that predispose to ER-negative disease, of which five SNPs were only or most strongly associated with risk of TN disease (rs4245739, rs10069690, rs74911261, rs11374964, and rs67397200) [6,7]. We further confirmed these five SNPs to be most strongly associated with TN disease and that they were associated with TN status in the extended model. ...
... Among the SNPs in cluster 3, rs3215401 was the only SNP that was not identified in a prior ERnegative GWAS [6,7]. rs3215401 was identified in a fine-mapping analysis of TERT and, consistent with our findings, reported to be most strongly associated with ER-negative disease but was also associated with ER-positive disease [23]. ...
Background: Genome-wide association studies have identified over 170 common breast cancer susceptibility loci, many of them with differential associations by estrogen receptor (ER). How these variants are related to other tumor features is unclear.
Methods: Analyses included 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 178 genotyped or imputed single nucleotide polymorphisms (SNPs). We used two-stage polytomous logistic regression models to evaluate SNPs 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: Nearly half of the SNPs (85 of 178) were associated with at least one tumor feature (false discovery rate <5%). Case-case comparisons identified ER and grade as the most common heterogeneity sources, followed by PR and HER2. Case-control comparisons among these 85 SNPs with intrinsic-like subtypes identified 65 SNPs strongly or exclusively associated at P<0.05 with luminal-like subtypes, 5 SNPs associated with all subtypes at differing strengths, and 15 SNPs primarily associated with non-luminal tumors, especially triple-negative (TN) disease. The I157T CHEK2 variant (rs17879961) was associated in opposite directions with luminal A-like (odds ratio (OR; 95% confidence interval (CI))=1.44 (1.31 to 1.59); P=9.26x10-14) and TN (OR (95% CI)=0.61 (0.47 to 0.80); P=2.55x10-4).
Conclusion: About half of the breast cancer susceptibility loci discovered in overall and ER-specific risk analyses have differential associations with clinical tumor features. These findings provide insights into the genetic predisposition of breast cancer subtypes and can inform subtype-specific risk prediction.
... In ovarian cancer, the A/Agenotype is associated with a significantly shortened disease-free and overall survival dependent on the ERstatus of the tumor [25]. Several genome-wide association studies (GWAS) revealed that the 1q32-locus, including SNP34091 (rs4245739), is a susceptibility locus in ERnegative breast cancer [26] and triple-negative breast cancer [27,28]. ...
... The genotype frequencies MDMX SNP34091 were in Hardy-Weinbergequilibrium (p > 0.5). The 1q32 locus where the MDMX gene resides has been shown to be a risk-factor of ERnegative breast cancer [26,28]. We therefore asked whether the impact of the respective alleles of MDMX SNP34091 might be dependent on the ER-expression status of the tumor. ...
... Therefore, it seems reasonable to assume the SNP285 status is an additional factor for risk stratification for patients in the intermediate risk group. Like SNP309 in the MDM2 gene, SNPs in the MDMX gene are apparently correlated with early age-atdiagnosis and risk of breast cancer dependent on the ERexpression status [26,27,31,41]. In our patient cohort, the homozygous A-allele of MDMX SNP31826 associates with an 11 years earlier age-at-diagnosis only in ERnegative breast cancers. ...
Background:
Genetic factors play a substantial role in breast cancer etiology. Genes encoding proteins that have key functions in the DNA damage response, such as p53 and its inhibitors MDM2 and MDMX, are most likely candidates to harbor allelic variants that influence breast cancer susceptibility. The aim of our study was to comprehensively analyze the impact of SNPs in the TP53, MDM2, and MDMX genes in conjunction with TP53 mutational status regarding the onset and progression of breast cancer.
Methods:
In specimen from 815 breast cancer patients, five SNPs within the selected genes were analyzed: TP53 - Arg72Pro (rs1042522), MDM2 - SNP285 (rs2279744), SNP309 (rs117039649); MDMX - SNP31826 (rs1563828), and SNP34091 (rs4245739). Classification of the tumors was evaluated by histomorphology. Subtyping according hormone receptor status, HER2-status and proliferation rate enabled provision of the clinico-pathological surrogate of intrinsic subtypes.
Results:
The homozygous C-allele of MDM2 SNP285 was significantly associated with a younger age-at-diagnosis of 44.2 years, in contrast to G/G- and G/C-patients (62.4, 62.7 yrs., respectively; p = 0.0007; log-Rank-test). In contrast, there was no difference regarding the age-at-diagnosis for patients with the respective genotypes of MDM2 SNP309 (p = 0.799; log-Rank-test). In patients with estrogen receptor (ER)-positive and TP53-mutated tumors, however, the T/T-genotype of the MDM2 SNP309 was significantly associated with an earlier average age-at-diagnosis compared with T/G+G/G-patients (53.5 vs. 68.2 yrs; p = 0.002; log-Rank-test). In the triple-negative subgroup, the G/G-patients had an average age-at-diagnosis of 51 years compared with 63 years for SNP309T carriers (p = 0.004; log-Rank-test) indicating a susceptibility of the G/G genotype for the development of triple negative breast cancer. Patients with the A/A-genotype of MDMX SNP31826 with ER-negative tumors were diagnosed 11 years earlier compared with patients and ER-positive tumors (53.2 vs. 64.4 yrs; p = 0.025, log-Rank-test). Furthermore, in luminal B-like patients (HER2-independent) the C/C-genotype of MDMX SNP34091 was significantly correlated with a decreased event-free survival compared with the A/A-genotype (p < 0.001; log-Rank-test).
Conclusions:
We showed that SNPs in the MDM2 and MDMX genes affect at least in part the onset and progression of breast cancer dependent on the ER-status. Our findings provide further evidence for the distinct etiological pathways in ER-negative and ER-positive breast cancers.
... That data was derived from cases and controls of European ancestry from studies using the Breast Cancer Association Consortium (BCAC) [17] and Consortium of Investigators of Modi ers of BRCA1/2 (CIMBA) [18] ( Table 1). We identi ed the most recent BCa GWAS [16] that expanded on previous BCAC GWAS [19][20][21]. We performed LD expansion using LDlinkR [22] for the European population. ...
... Optimization of gene-cell proposals against breast data using GA To describe the mechanisms of cancer risk based on population genetics of BCa, we acquired 206 lead variants of European ancestry [16, [19][20][21] (Table 1). For each variant, we identi ed proxy SNPs in LD plus candidate genes (described in Methods). ...
Background: With recent advances in single cell technology, high-throughput methods provide unique insight into disease mechanisms and more importantly, cell type origin. Here, we used multi-omics data to understand how genetic variants from genome-wide association studies influence development of disease. We show in principle how to use genetic algorithms with normal, matching pairs of single-nucleus RNA- and ATAC-seq, genome annotations, and protein-protein interaction data to describe the genes and cell types collectively and their contribution to increased risk.
Results: We used genetic algorithms to measure fitness of gene-cell set proposals against a series of objective functions that capture data and annotations. The highest information objective function captured protein-protein interactions. We observed significantly greater fitness scores and subgraph sizes in foreground vs.matching sets of control variants. Furthermore, our model reliably identified known targets and ligand-receptor pairs, consistent with prior studies.
Conclusions: Our findings suggested that application of genetic algorithms to association studies can generate a coherent cellular model of risk from a set of susceptibility variants. Further, we showed, using breast cancer as an example, that such variants have a greater number of physical interactions than expected due to chance.
... Recent studies identified a loss of breast cancer risk association after adjusting for BMI 29 . However, Garcia-Closas and colleagues tested the association with ER negative breast cancer risk after adjusting for BMI and observed no change 30 . We therefore explored the effects of the rs11075995 on the expression of both FTO and IRX3 in breast tissue. ...
... Interestingly, breast cancer risk association studies that have adjusted for BMI have demonstrated a dependence for variants at the rs11075995 locus on BMI status 29 . However, an independent relationship was described for ER negative breast cancer risk and BMI for rs11075995 30 , suggesting that variants in the same locus may have disease-specific risk profiles. ...
Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations ( p < 5 × 10 –8 ) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes ( CYP11B1, CYP17A1 HSD3B2 and STAR ) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO , suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.
... The 32 novel variants are labeled with arrow. The other significant variants are within +-500 or LD > 0.3 with previous reported variants. variants in overall analysisSignificant variants in subtypes analysisOverall analysis identified 22 novel variants BCAC TN and CIMBA BRCA1 carriers meta-analysis identified 2 novel variantsSignificant variants in BCAC TN and CIMBA BRCA1 carriers meta-analysisSubtypes analysis identified 8 novel variantsFigure 2. Heatmap and clustering of p-values from marker specific heterogeneity test for 32 breast cancer susceptibility loci. ...
... Genetic variance corresponds to heritability on the frailty-scale, which assumes the polygenetic log-additive model as the underlying model.2 Susceptibility variants included 178 variants identified or replicated in Nature 551, 92-94 (2017) and NatGenet 49, 1767Genet 49, -1778Genet 49, (2017 and 32 newly identified variants in this paper.3 Genetic variance of all reliably genome-wide imputable variants was estimated through LD-score regression described in NatGenet 47, 291-5 (2015). ...
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1,2,3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10−8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
... LGR6 has been widely reported to be an important stem cell marker in many cancer types that promotes the occurrence and progression of cancer. 19,20 Paradoxically, LGR6 has been reported to act as a tumor suppressor gene in colon and breast cancers. 21 25,26 Our results suggest that LGR6 may be a potential therapeutic target for ESCC, providing a potential therapeutic strategy by increasing the degradation or reducing the expression of LGR6 to interfere with tumor progression. ...
... The minimum required interaction score is 0.905 (very high confidence) ovarian cancer cells through this mechanism.18,19,26 LGR6 may contribute to the development and progression of ESCC by activating the Wnt/β-catenin signaling pathway, but further research is needed to confirm this hypothesis.However, the function of LGR6 in different cancers remains controversial.[19][20][21][22] Notably, the LGR6 PPI network showed thatLGR6 interacts with ZNRF3, RNF43, UBC, UBB and other protein molecules. ...
Background
Leucine‐rich repeat–coupled receptor 6 (LGR6) is a marker of the skin, nails, and other types of adult tissue stem cells and has been widely found to be related to the development and progression of a variety of cancer types. The clinical significance and biological function of LGR6 in esophageal squamous cell carcinoma (ESCC) have not been determined.
Methods
The expression of LGR6 at the transcriptional level was analyzed by searching the TCGA and UCSC data sets. Immunohistochemistry, WB, and q‐PCR were used to detect the expression of LGR6 in ESCC and adjacent normal tissues. LGR6 PPI networks and KEGG pathways were used to analyze the potential biological functions of LGR6.
Results
The expression of LGR6 in ESCC tissues was significantly higher than that in normal tissues and was negatively correlated with the differentiation degree of ESCC and the prognosis of the patients but not closely correlated with the TNM stage of ESCC. PPI networks showed that LGR6 had a close interaction with RSPO1, RSPO2, RSPO3, and RSPO4. KEGG pathway analysis showed that LGR6 activated the Wnt/β‐catenin signaling pathway by binding with RSPO ligands to promote the progression of ESCC.
Conclusion
LGR6 can serve as a potential diagnostic and prognostic marker for ESCC.
... Because of this complexity, cancer pathogenesis is not only determined by the amount of the constituent cells, but also depends on how these cells interact with each other and with their microenvironment in the body [4]. Currently used genome-wide association studies (GWAS) that sample a set of patients from a natural population have been instrumental for characterizing key somatic mutations that cause tumor growth [5][6][7][8], but these genes identified are merely associated with the overall symptom of cancer, not with the pattern and strength of ITH [9]. Also, genes derived from patients' normal tissues by GWAS may be related with cancer progression through a myriad of indirect pathways, rather than directly participate in this event as derivers [6]. ...
... As a complex disease, cancer is jointly controlled by genetic and environmental factors and their interactions through developmental pathways. A vast body of cancer research has used genomewide association studies (GWAS) to identify genetic loci associated with cancer risk by comparing differences of DNA sampled from a natural population [6][7][8][9]. However, despite our mounting knowledge gained from GWAS, an overwhelming success in understanding the genetic basis of this disease has still been largely far from our expectation. ...
Intratumoral heterogeneity (ITH) has been regarded as a key cause of the failure and resistance of cancer therapy, but how it behaves and functions remains unclear. Advances in single-cell analysis have facilitated the collection of a massive amount of data about genetic and molecular states of individual cancer cells, providing a fuel to dissect the mechanistic organization of ITH at the molecular, metabolic and positional level. Taking advantage of these data, we propose a computational model to rewire up a topological network of cell-cell interdependences and interactions that operate within a tumor mass. The model is grounded on the premise of game theory that each interactive cell (player) strives to maximize its fitness by pursuing a "rational self-interest" strategy, war or peace, in a way that senses and alters other cells to respond properly. By integrating this idea with genome-wide association studies for intratumoral cells, the model is equipped with a capacity to visualize, annotate and quantify how somatic mutations mediate ITH and the network of intratumoral interactions. Taken together, the model provides a topological flow by which cancer cells within a tumor cooperate or compete with each other to downstream pathogenesis. This topological flow can be potentially used as a blueprint for genetically intervening the pattern and strength of cell-cell interactions towards cancer control.
... GWAS have identified over 170 independent breast cancer susceptibility loci, many of which show differential associations by tumor subtypes, particularly ER-positive versus ER-negative or triple negative (TN) disease [1][2][3] . However, prior GWAS have not simultaneously investigated multiple, correlated tumor markers to identify additional source(s) of etiologic heterogeneity. ...
... Genetic variance corresponds to heritability on the frailty-scale, which assumes the polygenetic log-additive model as the underlying model.2 Susceptibility SNPs included 178 SNPs identified or replicated in Nature 551, 92-94 (2017) and Nat Genet 49, 1767-1778 (2017) and 32 newly identified SNPs in this paper.3 Genetic variance of all reliably genome-wide imputable variants was estimated through LD-score regression described in Nat Genet 47,291-5 (2015). ...
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal- and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
... Recent data from the Collaborative Oncological Gene-environment Study (COGS) identified SNP34091 in the 3 UTR of the human MDM4 gene, as a cancer risk locus in hormonally mediated cancers [8,9]. MDM4 is the most proximal MDM2 homolog and also a relevant p53-regulator endowed of oncogenic activity and as such altered in different human tumors [10]. ...
... SNP34091 is assumed to alter MDM4 levels by creating a putative target site for hsa-miR-191, a microRNA highly expressed in tumor tissues [11,12]. This SNP confers increased cancer risk in ER-negative breast cancer [8,13] and prostate cancer [9], and is correlated with poor overall (OS) and disease-free survival (DFS) in ER-negative ovarian cancer [11]. These data suggest that the estrogenic pathway can interfere with MDM4 levels and/or function. ...
Estrogen activity towards cancer-related pathways can impact therapeutic intervention. Recent omics data suggest possible crosstalk between estrogens/gender and MDM4, a key regulator of p53. Since MDM4 can either promote cell transformation or enhance DNA damage-sensitivity, we analysed in vivo impact of estrogens on both MDM4 activities. In Mdm4 transgenic mouse, Mdm4 accelerates the formation of fibrosarcoma and increases tumor sensitivity to cisplatin as well, thus confirming in vivo Mdm4 dual mode of action. Noteworthy, Mdm4 enhances chemo- and radio-sensitivity in male but not in female animals, whereas its tumor-promoting activity is not affected by mouse gender. Combination therapy of transgenic females with cisplatin and fulvestrant, a selective estrogen receptor degrader, was able to recover tumor cisplatin-sensitivity, demonstrating the relevance of estrogens in the observed sexual dimorphism. Molecularly, estrogen receptor-α alters intracellular localization of MDM4 by increasing its nuclear fraction correlated to decreased cell death, in a p53-independent manner. Importantly, MDM4 nuclear localization and intra-tumor estrogen availability correlate with decreased platinum-sensitivity and apoptosis and predicts poor disease-free survival in high-grade serous ovarian carcinoma. These data demonstrate estrogen ability to modulate chemo-sensitivity of MDM4-expressing tumors and to impinge on intracellular trafficking. They support potential usefulness of combination therapy involving anti-estrogenic drugs.
... More homogenous populations with specific subtypes of cancer are currently being investigated to generate more informative SNPs. It is interesting that many variants confer risks that differ by breast cancer subtypes suggesting that subtypespecific PRS might predict for a subtype specific disease [29][30][31][32][33][34]. In Jan 2019, Mavaddat and colleagues published data from 79 studies conducted by the BCAC. ...
... That makes the GWAS less powerful in predicting estrogenreceptor-negative subtypes. As a result, more efforts led by the Triple Negative Breast Cancer Consortium (TNBCC), among other groups are focusing specifically on identifying SNPs directly linked to triple negative disease [31][32][33][34]. Larger data sets for the GWAS analysis are still however needed for prediction of less common disease subtypes [36]. ...
Purpose of Review
Breast cancer is a complex disease that is fueled by genetic as well as non-genetic factors. As data risk estimates become better, stratifying a woman’s risk for breast cancer can lead to better prevention strategies. The purpose of this review is to introduce the polygenic risk score (PRS) and shed light on its clinical applications as well as shortcomings in the field of breast cancer prevention.
Recent Findings
A PRS combines relevant single-nucleotide polypeptides (SNPs) and generates an estimated risk of a specific cancer. It has the ability of questioning the whole genome and incorporating the added benefit of an individualized assessment. The PRS has become a part of the risk assessment evaluation without being officially approved.
Summary
The benefit of the PRS can be substantial and holds the promise of improved breast cancer prevention. However, more studies are needed to justify its routine use in our clinics.
Trial Registration
NCT03688204
... Starting from the assumption that the manifestation of breast cancer can be based on the genetic dispositions of certain individuals, it seemed interesting to compare the population-genetic structure of cancer patients with the population-genetic structure of healthy individuals (15)(16)(17)(18). ...
Background:
Breast cancer in women is the second most common and accounts for approximately 18% of all malignant tumors in women worldwide. The etiology of breast cancer is not clear enough. Starting from the assumption that the manifestation of breast cancer may have a multifactorial model, this article compares the population-genetic structure of patients (experimental group) with the population-genetic structure of healthy population (control group).
Objective:
The aim of the study was to examine the possible genetic basis of the Rh factor relationship with selected homozygous-recessive traits of females with breast cancer, and to diagnose the probability (assess the risk) of developing the disease in healthy women by analyzing homozygous-recessive traits (HRT).
Methods:
This are an anthroposcopic-qualitative study that included two groups of subjects, experimental and control (a total of 80 subjects). An analysis of the percentages within each group was performed using the Chi-square test. The results are presented in tables, and the accepted level of significance is at the level of p <0.05.
Results:
In the group of Rh+ subjects, the correlation of this type of Rh factor with the breast cancer was proven, given the frequency of the phenotype of homozygous-recessive traits in them. A statistically significant difference was found for 4 traits, and three are also close to the set significance level. In subjects with Rh- factor, a statistically significant difference was found for only one trait (absence of mallets on the phalanges).
Conclusion:
Although the number of subjects was relatively small, we can conclude that in the experimental group a higher frequency of recessive phenotypes for the examined traits was recorded, which indicates the genetic load of the subjects from this group. Correlation with Rh factor was observed in the case of subjects of the experimental group with Rh+ factor.
... Many of which have been associated with a specific tumour category, such as ER positiveness or Her2 amplification. However, no clear subcategories exist despite tumour heterogeneity and differences in clinical response to treatment and tumour relapse within the same category [8][9][10]. Interestingly, alternative splicing is an emerging source of new biomarkers and therapeutic targets in cancer [11][12][13][14][15]. ...
Background
Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers.
Results
Transcriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype.
Conclusions
Using a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.
... 30,31 However, a genome-wide association study with 10,707 BC and 76,646 controls identified rs4245739 polymorphism as an important estrogen receptor (ER) negative-specific BC risk locus. 32 Differences in BC types, sample sizes and races may 26 Obviously, the sample sizes and ethnicities were both different between our study and the Norwegian study. Another point was that eating habits and living environments were different. ...
Background
Studies show that MDM4 may play a pivotal role in colorectal cancer (CRC). Recently, a host of studies suggest that MDM4 gene rs4245739 polymorphism may modify the risk of different cancers.
Methods
In this study, we were interested whether MDM4 gene rs4245739 polymorphism correlated with the risk and clinical characteristics of CRC. Logistic regression was adopted to estimate the association of rs4245739 polymorphism and CRC risk.
Results
We enrolled 444 CRC patients and 530 controls and found MDM4 gene rs4245739 polymorphism may decrease the risk of CRC. Stratified analyses uncovered that this variant was connected to a less risk of CRC in females, non-drinkers, non-smokers, and people under 60 years old. Additionally, rs4245739 polymorphism was related to TNM staging, pathological type, tumor size, and location of CRC. Furthermore, this polymorphism was significantly linked with the survival of CRC.
Conclusion
Totally, this study suggests that MDM4 rs4245739 polymorphism is linked with the risk and clinical characteristics of CRC.
... Nous avons montré que pour 96 % des SNPs identifiés par les études GWAS réalisées en population générale132,137,138,141,158,159,161,163,165, , il n'a pas été possible de mettre en évidence une interaction significative entre la présence d'une mutation BRCA1/2 et des SNPs.Ces résultats suggèrent que ces SNPs sont également associés au risque de cancer du sein dans la population des femmes porteuses d'une mutation BRCA1/2 avec des effets similaires à ceux trouvés dans la population générale. Cependant, il existe une interaction significative entre 10 SNPs connus comme étant associés au cancer du sein dans la population générale et les mutations BRCA1/2, suggérant que ces SNPs ont un effet différent chez les sujets porteurs sont en fait des SNPs non modificateurs du risque de cancer du sein dans la population des porteurs d'une mutation de BRCA1/2est en adéquation avec le fait que le PRS BCAC prédit moins bien dans cette population 164 .rs736596 ...
Avoir une apparentée atteinte d’un cancer du sein (CS) multiplie par 2 le risque de développer un CS. Environ 20 % du risque familial de CS est attribué à une mutation fortement pénétrante dans les gènes BRCA1 ou BRCA2. D’autres gènes connus, comme ATM ou TP53, ainsi que des variants génétiques fréquents (SNP) identifiés dans des études pangénomiques (GWAS) réalisées en population générale, expliqueraient 30 % supplémentaires des cas familiaux. La majorité des formes familiales de CS restent donc inexpliquées. Par ailleurs, il existe de fortes variations du risque parmi les porteurs d’une mutation BRCA1/2. Il a été montré que certains SNP identifiés dans les GWAS modifient leur risque. Cependant, l'effet propre de ces SNP n'a pu être estimé puisque ces études ont été réalisées chez les porteurs de mutation BRCA1/2. Dans une première partie de ma thèse, j’ai développé une stratégie intégrant aux analyses sur les facteurs génétiques des facteurs « environnementaux ». Cette stratégie a été utilisées pour analyser les données de l'étude GENESIS qui inclut des paires de sœurs atteintes de CS et sans mutation BRCA1/2 et des témoins de population générale. Elle regroupe 5 000 cas de CS et témoins génotypés pour les 200 000 SNP de la puce iCOGS. Les femmes de GENESIS ont été réparties dans des groupes selon leur profil d’expositions aux radiations ou aux facteurs gynéco-obstétriques. Alors que l’analyse stratifiée sur les groupes construits à partir des expositions aux facteurs gynéco-obstétriques ne nous permet pas de mettre en évidence de potentiels SNPs spécifiques, l’analyse stratifiée sur les groupes construits à partir des expositions aux radiations a permis de mettre en évidence des SNPs spécifiques potentiels aux femmes non exposées, dans les gènes XRCC4 et MAGI1, et à celle fortement exposées aux radiations, dans le gène FGFR2, déjà trouvés en population générale.Le deuxième objectif de ma thèse visait à optimiser la caractérisation des gènes BRCA1/2 en étudiant leurs interactions avec des SNPs modificateurs à partir des données des consortia internationaux CIMBA (Consortium of Investigators of Modifiers of BRCA1/2) et BCAC (Breast Cancer Association Consortium). J’ai développé une stratégie d’analyse GWAS case-only, comparant la fréquence de 60 212 cas de cancer du sein de la population générale (BCAC) et 13,007 cas porteurs d’une mutation BRCA1/2 (CIMBA). J’ai identifié 4 nouvelles régions associés au CS chez les femmes porteuses d’une mutation BRCA1 et 4 autres chez les femmes porteuses d’une mutation BRCA2. Les gènes MADD, SPI1 et EIF1, déjà associées à la biologie du cancer du sein dans d’autres études, ont été prédits par l’outil INQUISIT comme étant des gènes cibles des potentiels variants causaux se trouvant dans la région 11p11.2 associée au statut BRCA1.Ces nouveaux SNPs mis en évidence pourraient être utilisés pour améliorer les prédictions de risque des PRS (Polygénic Risk Score). Les analyses prenant en compte des profils d’exposition devraient être poursuivies sur des études de grande dimension. Les modèles pourraient alors évoluer vers une adaptation des PRS en fonction des profils d’expositions des femmes et cela tout au long de leur vie.
... EBF1 is involved in the regulation of metabolic and inflammatory signaling pathways, and the loss of gene function results in impaired insulin and inflammatory signaling (Griffin et al., 2013). EBF1 plays a role in a variety of diseases including breast cancer (Fernandez-Jimenez et al., 2017;Garcia-Closas et al., 2013;Michailidou et al., 2013), coronary artery disease (Ehret et al., 2011;Li et al., 2017;Singh et al., 2015;Wain et al., 2011), Hodgkin lymphoma (Bohle et al., 2013), multiple sclerosis (Martinez et al., 2005;Sombekke et al., 2010), and leukemia (Heltemes-Harris et al., 2011;Mesuraca et al., 2015;Welsh et al., 2018). ...
Background:
Longevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB).
Methods:
From an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (<.01 population frequency) variants shared by at least one elderly cousin pair in a region likely to be identical by descent were identified as candidates. Ingenuity Variant Analysis was used to prioritize putative causal variants based on quality control, frequency, and gain or loss of function. The variant frequency was compared in healthy cohorts and in an Alzheimer's disease cohort. Remaining variants were filtered based on their presence in genes reported to have an effect on the aging process, aging of cells, or the longevity process. Validation of these candidate variants included tests of segregation on other elderly relatives.
Results:
Fifteen rare candidate genetic variants spanning 17 genes shared within cousins were identified as having passed prioritization criteria. Of those variants, six were present in genes that are known or predicted to affect the aging process: rs78408340 (PAM), rs112892337 (ZFAT), rs61737629 (ESPL1), rs141903485 (CEBPE), rs144369314 (UTP4), and rs61753103 (NUP88 and RABEP1). ESPL1 rs61737629 and CEBPE rs141903485 show additional evidence of segregation with longevity in expanded pedigree analyses (p-values = .001 and .0001, respectively).
Discussion:
This unique pedigree analysis efficiently identified several novel rare candidate variants that may affect the aging process and added support to seven genes that likely contribute to longevity. Further analyses showed evidence for segregation for two rare variants, ESPL1 rs61737629 and CEBPE rs141903485, in the original longevity pedigrees in which they were initially observed. These candidate genes and variants warrant further investigation.
... In Egypt, BC is the prevalent female cancer with a percentage of about 38.8% of all cancers types in women, with increasing mortality rates (up to 1.3% in the years from 2000 to 2011 (2,3). The risk for developing BC has been reported to be associated with many susceptible single nucleotide polymorphisms (SNPs) (4,5). Therefore, deep insights into the mechanisms underlying the involvement of SNPs in cancer susceptibility may lead to better understanding of the molecular pathogenesis of the disease. ...
Two single nucleotide polymorphisms (SNPs) of
matrix metalloproteinase (MMPs) 3 and 9 are functionally
implicated in the progression of various types of cancer, including breast cancer (BC). However, the roles of these SNPs remain controversial. In addition, they also vary between one population and another. Therefore, the present study aimed to investigate the possible association between MMP3‑1171 5A/6A and MMP9‑1562 CT SNPs and the risk of BC among Egyptians, and to elucidate the alteration of MMP3 and MMP9 gene expression in patients with BC. The present case‑control study enrolled 162 patients with BC and 146 control subjects. Restriction fragment length polymorphism‑PCR was
performed for analysis of the selected SNPs, gene expression of MMP3 and MMP9 was also assessed in 50 patients and 50 control subjects by reverse transcription‑quantitative PCR. The frequencies of 5A/6A genotype and 5A allele of MMP3 were significantly higher in patients with BC compared with in healthy subjects. On the other hand, the distributions of MMP9 genotypes and alleles were not significantly different among patients and healthy subjects. Compared with healthy subjects, the expression levels of the two genes were found to be upregulated in patients with BC. Therefore, the present study indicated that MMP3‑1171 5A/6A SNP, not MMP9‑1562 C>T SNP may be a risk factor for developing BC among Egyptian females.
... In a study on 10,706 patients and 76,647 healthy people, an association was found between rs11075995 polymorphism and the risk of BC (OR = 1.11, 95% CI: 1.07-1.15) [25]. ...
Introduction: The fat mass and obesity-associated (FTO) gene may be associated with breast cancer risk. This study aimed to systematically investigate the association between FTO gene polymorphisms and breast cancer and the possible role of estrogen in this association.
Areas covered: We performed an extensive search of electronic databases such as PubMed, Science Direct, Scopus, and Cochran for published original studies on the association of FTO gene polymorphisms with breast cancer risk. Keywords such as breast cancer and/or FTO gene and/or polymorphism were used in order to identify the related articles. We excluded studies unrelated to the FTO genotype and the outcome of breast cancer.
Expert opinion: FTO gene may have a significant association with the risk of breast cancer. The association between FTO gene polymorphisms and breast cancer were influenced by the status of estrogen receptors. Estrogen may promote breast cancer cell proliferation through up-regulation of FTO gene expression and activation of the PI3K/Akt signaling pathway in estrogen receptor positive patients. Further studies are warranted to identify the underlying mechanisms and signaling pathways involved in the interactions between FTO gene, estrogen, and the risk of breast cancer.
... 15,22,23 A total of 205 common breast cancer susceptibility variants were selected for evaluation of G x E interactions (Supplementary Table 2, available as Supplementary data at IJE online). These variants have been associated with breast cancer risk either through GWAS [24][25][26][27][28][29][30][31][32][33][34] or by fine mapping of associated regions. [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52] Of these, 72 were identified through the OncoArray project and had not been previously evaluated for G x E interactions. ...
Background Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. Methods Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. Results Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10–4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10–5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. Conclusions Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
... 15,22,23 A total of 205 common breast cancer susceptibility variants were selected for evaluation of G x E interactions (Supplementary Table 2, available as Supplementary data at IJE online). These variants have been associated with breast cancer risk either through GWAS [24][25][26][27][28][29][30][31][32][33][34] or by fine mapping of associated regions. [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52] Of these, 72 were identified through the OncoArray project and had not been previously evaluated for G x E interactions. ...
Background:
Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.
Methods:
Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.
Results:
Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.
Conclusions:
Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
... Twin studies and familial studies suggested that heredity may account for ~49% of the risk of familial breast cancer [2][3][4]. To date, over 168 breast cancer risk loci have been identified by genomewide association studies (GWAS) of breast cancer [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]; yet, inherited variants of germline mitochondrial DNA (mtDNA) have not been fully examined in relation to breast cancer susceptibility. To our knowledge, no study to date has comprehensively examined the relationship between the mitochondrial genome variants and breast cancer risk in multiple ethnic populations. ...
Background
The mitochondrial genome encodes for thirty-seven proteins, among them thirteen are essential for the oxidative phosphorylation (OXPHOS) system. Inherited variation in mitochondrial genes may influence cancer development through changes in mitochondrial proteins, altering the OXPHOS process and promoting the production of reactive oxidative species.
Methods
To investigate the association between mitochondrial genetic variation and breast cancer risk, we tested 314 mitochondrial SNPs (mtSNPs), capturing four complexes of the mitochondrial OXPHOS pathway and mtSNP groupings for rRNA and tRNA, in 2,723 breast cancer cases and 3,260 controls from the Multiethnic Cohort Study.
Results
We examined the collective set of 314 mtSNPs as well as subsets of mtSNPs grouped by mitochondrial OXPHOS pathway, complexes, and genes, using the sequence kernel association test and adjusting for age, sex, and principal components of global ancestry. We also tested haplogroup associations using unconditional logistic regression and adjusting for the same covariates. Stratified analyses were conducted by self-reported maternal race/ethnicity. No significant mitochondrial OXPHOS pathway, gene, and haplogroup associations were observed in African Americans, Asian Americans, Latinos, and Native Hawaiians. In European Americans, a global test of all genetic variants of the mitochondrial genome identified an association with breast cancer risk (P = 0.017, q = 0.102). In mtSNP-subset analysis, the gene MT-CO2 (P = 0.001, q = 0.09) in Complex IV (cytochrome c oxidase) and MT-ND2 (P = 0.004, q = 0.19) in Complex I (NADH dehydrogenase (ubiquinone)) were significantly associated with breast cancer risk.
Conclusions
In summary, our findings suggest that collective mitochondrial genetic variation and particularly in the MT-CO2 and MT-ND2 may play a role in breast cancer risk among European Americans. Further replication is warranted in larger populations and future studies should evaluate the contribution of mitochondrial proteins encoded by both the nuclear and mitochondrial genomes to breast cancer risk.
... Moreover, there is growing evidence that defects in HRR can lead to increased dependence on altEJ for repair, particularly in the context of fork stalling during replication stress (26,54). In addition to its relationship with HRR, altEJ may also be synthetic lethal with c-NHEJ. ...
Repair of DNA damage protects genomic integrity, which is key to tissue functional integrity. In cancer, the type and fidelity of DNA damage response is the fundamental basis for clinical response to cytotoxic therapy. Here we consider the contribution of transforming growth factor-beta (TGFβ), a ubiquitous, pleotropic cytokine that is abundant in the tumor microenvironment, to therapeutic response. The action of TGFβ is best illustrated in head and neck squamous cell carcinoma (HNSCC). Survival of HNSCC patients with human papilloma virus (HPV) positive cancer is more than double compared to those with HPV-negative HNSCC. Notably, HPV infection profoundly impairs TGFβ signaling. HPV blockade of TGFβ signaling, or pharmaceutical TGFβ inhibition that phenocopies HPV infection, shifts cancer cells from error-free homologous-recombination DNA double-strand-break (DSB) repair to error-prone alternative end-joining (altEJ). Cells using altEJ are more sensitive to standard of care radiotherapy and cisplatin, and are sensitized to PARP inhibitors. Hence, HPV-positive HNSCC is an experiment of nature that provides a strong rationale for the use of TGFβ inhibitors for optimal therapeutic combinations that improve patient outcome.
... The respective roles of the BRCA1/2 proteins as upstream mediators and more downstream repair machinery respectively may well be reflected in the seriousness of the resultant tumours and the difference in lifetime risks. Common, low-penetrance variants in BRCA2 are associated with risk of breast, ovarian and prostate cancer (44)(45)(46)(47)(48), but no equivalent common variants have been found in BRCA1. Could this indicate that BRCA1 gene variants directly affect cell viability and hence are so deleterious they cannot become common in the population? ...
In this short review, we examine the overlap between genes known to be mutated in the germlines of individuals at risk of breast, ovarian and prostate cancers and their positions in DNA damage repair pathways. Cancer risk mutations have been consistently reported in certain genes at the top of these pathways, but none have been reported in others. We consider whether some of these gene products are too crucial to life for mutations to be tolerated, whilst others, further down the pathways, are less essential.
... Existing studies have demonstrated that more than 80 genetic variants or single nucleotide polymorphisms (SNPs) are associated with breast cancer risk. [3][4][5][6] On the other hand, a growing body of literature has shown that racial-ethnic identity is responsible for breast cancer risk and outcome. [7] There are racial disparities in Iranian population. ...
Background:
Breast cancer is one of the most frequent women malignancies in the world. The cytochrome P450 1A1 (CYP1A1) is a key enzyme in xenobiotics metabolism. Moreover, CYP1A1 plays a critical role in the etiology of breast cancer by involving in 2-hydroxylation of estrogen. Therefore, single-nucleotide polymorphisms (SNPs) of its coding gene have been verified to be important in cancer susceptibility. The aim of the study was to evaluate the association of CYP1A1 M2 (A2455G) includes rs1048943 of this SNP polymorphism with the risk of breast cancer in Mazandaran province.
Methods:
Ninety-six breast cancer patients with known clinicopathological characters and 110 healthy women as control were genotyped for CYP1A1 M2 polymorphisms by the restriction fragment length polymorphism technique.
Results:
The analysis of CYP1A1 gene (polymorphism M2) showed that the frequency of homozygous wild genotypes (AA), heterozygous (AG), and mutant genotype (GG) in the patient group, respectively, 78%, 22%, and 0%, and also the frequency of genotypes AA, AG, and GG in healthy included 82%, 16%, and 2%, respectively. Statistical analysis by Logistic regression model at P < 0.05 showed no significant correlation between polymorphisms in CYP1A1M2 and breast cancer risk (odds ratio = 0.84, confidence interval = 0.33-2.17).
Conclusions:
The results indicated that the M2 allelic genotypes were significantly associated neither with breast cancer risk nor with clinicopathological characteristics in Mazandaran province.
... Six SNPs were associated with increased risk (P<10 −5 ), including SNPs in or near the fibroblast growth factor receptor 2 (FGFR2; rs2981582) gene, lymphocyte-specific protein (LSP1; rs3817198), mitogen-activated protein kinase kinase kinase 1 (MAP3K1; rs889312), and tox high mobility group box family member 3 (TOX3; rs12443621 and rs8051542) and in the chromosome 8q24 region (rs13281615 [60]. In a second metaanalysis of three GWAS including 4,193 ER-breast cancer cases and 35,194 controls, combined with 40 follow-up studies, variants at rs4245739 located in the 3 region of the mouse double minute 4 homolog (MDM4) oncogene on chromosome 1q32.1 seemed to be specific to TNBC [16]. In addition to the loci summarized above, a GWAS approach identified the 19p13 chromosomal region as a modifier of breast cancer risk in BRCA1 mutation positive individuals [23]. ...
Triple negative breast cancer (TNBC), representing 10-15% of breast tumors diagnosed each year, is a clinically defined subtype of breast cancer associated with poor prognosis. The higher incidence of TNBC in certain populations such as young women and/or women of African ancestry and a unique pathological phenotype shared between TNBC and BRCA1-deficient tumors suggest that TNBC may be inherited through germline mutations. In this article, we describe genes and genetic elements, beyond BRCA1 and BRCA2 , which have been associated with increased risk of TNBC. Multigene panel testing has identified high- and moderate-penetrance cancer predisposition genes associated with increased risk for TNBC. Development of large-scale genome-wide SNP assays coupled with genome-wide association studies (GWAS) has led to the discovery of low-penetrance TNBC-associated loci. Next-generation sequencing has identified variants in noncoding RNAs, viral integration sites, and genes in underexplored regions of the human genome that may contribute to the genetic underpinnings of TNBC. Advances in our understanding of the genetics of TNBC are driving improvements in risk assessment and patient management.
... Traditional subtype identification has relied on detecting biomarkers or subphenotypes that distinguish subsets of individuals in a biologically meaningful way. For example, individuals with Type 1 diabetes (T1D) can be sub-grouped by auto-antibody positivity [6]; breast cancer has two well-known subtypes, estrogen receptor positive and negative, [7][8][9]; and psychiatric disorder patients can have di↵erent severities [10]. With the advent of large scale genome-wide association studies (GWAS) that have robustly identified thousands of risk variants for complex traits, multiple approaches have investigated the use of genetic risk variants to define classes of individuals that show genetic heterogeneity across subtypes [11][12][13][14][15][16]. ...
Genetic predisposition for complex traits is often manifested through multiple tissues of interest at different time points during their development. For example, the genetic predisposition for obesity could be manifested either through inherited variants that control metabolism through regulation of genes expressed in the brain, or through the control of fat storage by dysregulation of genes expressed in adipose tissue, or both. Here we describe a statistical approach that leverages tissue-specific expression quantitative trait loci (eQTLs) to prioritize the tissue of interest underlying the genetic predisposition of a given individual for a complex trait. Unlike existing approaches that prioritize tissues of interest for the trait in the population, our approach probabilistically quantifies the tissue-specific genetic contribution to the trait for a given individual. Through simulations using the UK Biobank genotype data, we show that our approach can predict the relevant tissue of interest accurately and can cluster individuals according to their tissue-specific genetic architecture. We analyze body mass index (BMI) and waist to hip ratio adjusted for BMI (WHRadjBMI) in the UK Biobank to identify individuals who have their genetic predisposition manifested through their brain versus adipose tissue, and adipose versus muscle tissue, respectively. Notably, we find that the individuals with a particular tissue of interest have specific phenotypic features beyond BMI and WHRadjBMI that distinguish them from random individuals in the data, demonstrating the role of tissue-specific genetic predisposition for these traits.
... Mutations in CDH1 [5], PTEN [6], and TP53 [7], which are associated with hereditary diffuse cancer, Cowden disease, and Li-Fraumeni syndrome, respectively, also contribute to high-risk predisposition of BC but are very rare. Low-penetrance genes, common polymorphisms [8,9], copy number variants [10][11][12], and epigenetic alterations [13,14] on familial BC risk are also suggested as constitutive risk factors but do not explain the missing fraction of familial heritability. ...
In addition to several well-established breast cancer (BC) susceptibility genes, the contribution of other candidate genes to BC risk remains mostly undefined. BARD1 is a potentially predisposing BC gene, however, the rarity of its mutations and an insufficient family/study size have hampered corroboration and estimation of the associated cancer risks. To clarify the role of BARD1 mutations in BC predisposition, a comprehensive case-control association study of a recurring nonsense mutation c.1690C>T (p.Q564X) was performed, comprising ~14,000 unselected BC patients and ~5900 controls from Polish and Belarusian populations. For comparisons, two BARD1 variants of unknown significance were also genotyped. We detected the highest number of BARD1 variants in BC cases in any individual BARD1-specific study, including 38 p.Q564X mutations. The p.Q564X was associated with a moderately increased risk of BC (OR = 2.30, p = 0.04). The estimated risk was even higher for triple-negative BC and bilateral BC. As expected, the two tested variants of unknown significance did not show significant associations with BC risk. Our study provides substantial evidence for the association of a deleterious BARD1 mutation with BC as a low/moderate risk allele. The p.Q564X was shown to be a Central European recurrent mutation with potential relevance for future genetic testing.
... 28,29 Paradoxically, two literatures have reported that LGR6 potentially functioned as a tumor suppressor in colon cancer and breast cancer. 24,30 These findings suggest that the pro-and anti-tumor roles of LGR6 are tumor type dependent. In ovarian cancer, LGR6 has been found to be associated with the development and progression of high-grade serous ovarian carcinoma. ...
... Here, we evaluate the joint associations on breast cancer risk of a 77-SNP PRS for breast cancer and quantitative mammographic density measures, including percent density and absolute dense area, adjusted for age and BMI, using data from eight studies in the Breast Cancer Association Consortium (BCAC) [1,[23][24][25][26][27]. ...
Background
Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.
Methods
Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.
Results
Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38–1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28–1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45–1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.
Conclusions
The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
Electronic supplementary material
The online version of this article (10.1186/s13058-019-1138-8) contains supplementary material, which is available to authorized users.
... 28,29 Paradoxically, two literatures have reported that LGR6 potentially functioned as a tumor suppressor in colon cancer and breast cancer. 24,30 These findings suggest that the pro-and anti-tumor roles of LGR6 are tumor type dependent. In ovarian cancer, LGR6 has been found to be associated with the development and progression of high-grade serous ovarian carcinoma. ...
Leucine-rich-repeat-containing G protein-coupled receptors (LGRs) have been widely found to be implicated with development and progression in multiple cancer types. However, the clinical significance and biological functions of LGR6 in ovarian cancer remains unclear. In this study, LGR6 expression was mainly examined by immunohistochemistry. Functional assays in vitro and animal experiments in vivo were carried out to explore the effect of LGR6 on cancer stem cell (CSC) characteristics and chemotherapeutic responses in ovarian cancer cells. Luciferase assays and GSEA were used to discern the underlying mechanisms contributing to the roles of LGR6 in ovarian cancer. Here, we reported that LGR6 was upregulated in ovarian cancer, which positively correlated with poor chemotherapeutic response and progression survival in ovarian cancer patients. Loss-of-function assays showed that downregulating LGR6 abrogated the CSC-like phenotype and chemoresistance in vitro. More importantly, silencing LGR6 improved the chemoresistance of ovarian cancer cells to cisplatin in vivo. Mechanistic investigation further revealed that silencing LGR6 inhibited stemness and chemoresistance by repressing Wnt/β-catenin signaling. Collectively, our results uncover a novel mechanism contributing to LGR6-induced chemotherapeutic resistance in ovarian cancer, providing the evidence for LGR6 as a potential therapeutic target in ovarian cancer.
BACKGROUND
Estrogen is involved in both bone metabolism and breast cancer proliferation. However, evidence about the risk of breast cancer according to women's bone mineral density (BMD) is scarce, and little is known about their causal associations.
METHODS
Women participating in the UK Biobank cohort were used to investigate the association between BMD and the risk of breast cancer using Cox regression models. Instrumental variants associated with estimated BMD (eBMD) were extracted from genome‐wide association studies with European ancestry. Logistic regression was used to calculate the genetic association with breast cancer in the UK Biobank and 2‐sample Mendelian randomization (MR) analyses to assess their causal associations with breast cancer. Finally, the pleiotropic conditional false discovery rate (cFDR) method was conducted to further detect common genetic variants between BMD and breast cancer.
RESULTS
Compared with the general population, postmenopausal women with BMD T scores <−2.5 had a lower risk of breast cancer (hazard ratio [HR], 0.77; 95% CI, 0.59‐1.00), and this effect was stronger in women with fracture (HR, 0.31; 95% CI, 0.12‐0.82). In MR analysis, no causal associations between eBMD and breast cancer were observed. The cFDR method identified 63 pleiotropic loci associated with both BMD and breast cancer, of which CCDC170, ESR1, and FTO might play crucial roles in their pleiotropy.
CONCLUSIONS
An association between BMD and the risk of postmenopausal breast cancer in the UK Biobank was observed, whereas no evidence supported their causal association. Instead, their association could be explained by pleiotropic genetic variants leading to the pathology of osteoporosis and breast cancer.
Aim:
The mouse double minute 4 (MDM4) may contribute to tumorgenesis by inhibiting p53 tumor suppressor activity. This study was designed to investigate whether MDM4 polymorphisms could affect susceptibility to esophageal squamous cell carcinoma (ESCC) and the survival of ESCC patients in a population from Cixian high-incidence region of northern China, which has not been explored.
Methods:
MDM4 rs1380576 and rs4245739 were genotyped by polymerase chain reaction-ligase detection reaction (PCR-LDR) in 568 ESCC patients and 578 controls.
Results:
Compared to rs1380576 C/C genotype, C/G genotype was associated with decreased risk of ESCC (odds ratio [OR] = 0.761, 95% confidence interval [CI] = 0.595-0.973). Compared to rs4245739 A/A genotype, A/C or C/C genotype was related to increased susceptibility to ESCC (OR = 1.551, 95% CI = 1.001-2.402). Individuals with GC haplotype had significantly higher risk of ESCC than those with CA or GA haplotype (OR = 1.598, 95% CI = 1.048-2.438). Neither rs1380576 nor rs4245739 influenced the survival of ESCC patients.
Conclusion:
rs1380576 and rs4245739 may be used to predict susceptibility to ESCC for population in Cixian high-incidence region.
Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal “at risk” breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman’s risk of breast cancer.
Purpose
The study aims to provide a comprehensive account of the association of five MDM4 gene polymorphisms (rs1380576, rs1563828, rs10900598, rs11801299, and rs4245739) with susceptibility to cancer.
Methods
A literature search for eligible candidate gene studies published before 27 February 2021 was conducted in PubMed, Medline and Web of Science. The following combinations of main keywords were used: (MDM4 OR MDMX OR HDMX OR mouse double minute 4 homolog) AND (polymorphism OR mutation OR variation OR SNP OR genotype) AND (cancer OR tumor OR neoplasm OR malignancy OR carcinoma OR adenocarcinoma). Potential sources of heterogeneity were sought out via meta-regression, subgroup and sensitivity analysis.
Results
Overall, a total of 15 articles with 21,365 cases and 29,280 controls for five polymorphisms of the MDM4 gene were enrolled. In the stratified analysis of rs1380576, we found that Asians might have less susceptibility to cancer. We found that rs4245739 was correlated with a decreased risk of cancer for Asians and breast cancer susceptibility. However, for other polymorphisms, the results showed no significant association with cancer risk.
Conclusion
MDM4 rs1380576 polymorphism is negatively associated with the risk of cancer in the Asian population. MDM4 rs4245739 polymorphism is inversely associated with cancer risk for Asians and breast cancer susceptibility.
In recent years, collaboration among researchers in the field of cancer epidemiology has been accelerating in various forms. Here, we review recent trends in international collaborative research activities in the cancer epidemiology field in Japan. These include not only support for other countries with less developed cancer statistics infrastructures, but also large-scale compilations and international comparisons through collaborative studies, as well as integration with analytical epidemiology and clinical research. Formation of international cohort consortia and estimates of cancer and risk factors in each country have contributed to raising the skill levels of cancer epidemiologists as well as to expanding research networks and activities among cancer epidemiologists. Molecular and genome epidemiological studies on cancer have progressed over decades and these continue to increase in size and dimension. Application of evidence from this area in prevention is still underway and needs further effort. Japanese epidemiologists have great potential to assume international leadership roles by taking advantage of the uniqueness, originality and characteristics of Japanese cohorts.
This review summarises not only the latest evidence on prevention, but also the current research on the treatment of early-stage breast cancer patients. Recent years have seen a growing body of evidence on the risk of high- and moderate-penetrance breast cancer susceptibility genes. A large international consortium has now been able to further refine the answer to the question of the significance of the so-called panel genes. Moreover, the data on treatment selection regarding endocrine efficacy and the decision for or against chemotherapy have also been advanced markedly. There is also new data on adjuvant CDK4/6 (cyclin-dependent kinase 4/6) inhibitors, which are standard in first-line treatment in patients with metastatic HER2-negative, hormone receptor-positive (HR+) breast cancer. For other therapies such as immune checkpoint inhibitors, which have successfully improved the rate of pathologic complete response (pCR) in neoadjuvant treatment settings for patients with triple-negative breast cancer (TNBC), there is a growing understanding of the quality of life and side effects. This is especially important in situations where patients could possibly be cured without such a regimen.
Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10 ⁻⁸ , at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD , SP11 and EIF1 , genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.
The treatment of patients with early breast cancer has always been characterised by escalation by new therapies and de-escalation through identification of better treatment regimens or introduction of better tools to estimate prognosis. Efforts in some of these areas in the last few years have led to solid data. The results of the large studies of de-escalation through use of multi-gene tests are available, as are the results of some studies that investigated the new anti-HER2 substances T-DM1 and pertuzumab in the early treatment situation. Several large-scale studies examining the role of CDK4/6 inhibitors will soon be concluded so innovations can be anticipated in this area also. This review article will summarise and classify the results of the latest publications.
Breast cancer risk assessment is important in order to identify individuals at extremely high risk who would be potential candidates for prophylactic surgery or preventive therapy, those at a moderately enhanced risk who might benefit from enhanced surveillance and potentially those at sufficiently low risk as to not require surveillance or risk management. Women with a substantial family history of the disease qualify for genetic testing of high-risk BRCA1/2 genetic alterations. For women without mutations in high-risk genes, or without a large family history, the current state of the art for risk assessment combines classical questionnaire risk factors (including information on hormonal and reproductive factors), mammographic density and genetic testing through polygenic risk scores. Risk models for these components alone and their combination have shown a degree of accuracy in prediction of invasive breast cancer risk. In this chapter, we consider how risk models are calculated, their potential clinical use and the targets for research in the future to improve risk assessment in order to better inform risk management and surveillance.
Background
Genome wide association studies (GWAS) are greatly accelerating the pace of discovery of germline variants underlying the genetic architecture of sporadic breast cancer predisposition. We have built the first knowledge-base dedicated to this field and used it to generate hypotheses on the molecular pathways involved in disease susceptibility.
Methods
We gathered data on the common single nucleotide polymorphisms (SNPs) discovered by breast cancer risk GWAS. Information on SNP functional effect (including data on linkage disequilibrium, expression quantitative trait locus, and SNP relationship with regulatory motifs or promoter/enhancer histone marks) was utilized to select putative breast cancer predisposition genes (BCPGs). Ultimately, BCPGs were subject to pathway (gene set enrichment) analysis and network (protein-protein interaction) analysis.
Results
Data from 38 studies (28 original case-control GWAS enrolling 383,260 patients with breast cancer; and 10 GWAS meta-analyses) were retrieved. Overall, 281 SNPs were associated with the risk of breast cancer with a P-value <10E-06 and a minor allele frequency >1%. Based on functional information, we identified 296 putative BCPGs. Primary analysis showed that germline perturbation of classical cancer-related pathways (e.g., apoptosis, cell cycle, signal transduction including estrogen receptor signaling) play a significant role in breast carcinogenesis. Other less established pathways (such as ribosome and peroxisome machineries) were also highlighted. In the main subgroup analysis, we considered the BCPGs encoding transcription factors (n=36), which in turn target 252 genes. Interestingly, pathway and network analysis of these genes yielded results resembling those of primary analyses, suggesting that most of the effect of genetic variation on disease risk hinges upon transcriptional regulons.
Conclusions
This knowledge-base, which is freely available and will be annually updated, can inform future studies dedicated to breast cancer molecular epidemiology as well as genetic susceptibility and development.
Abbreviations
GWAS genome-wide association study
SNP single nucleotide polymorphism
BCPG breast cancer predisposition gene
LD linkage disequilibrium
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1–3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10−8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores. Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade.
This review is intended to present the latest developments in the prevention and treatment of early breast cancer. The risk of breast cancer can be increasingly better characterised with large epidemiological studies on genetic and non-genetic risk factors. Through new analyses, the evidence for high-penetrance genes as well as for low-penetrance genes was able to be improved. New data on denosumab and atezolizumab are available in the neoadjuvant situation as is a pooled appraisal of numerous studies on capecitabine in the curative situation. There is also an update to the overall survival data of pertuzumab in the adjuvant situation with a longer follow-up observation period. Finally, digital medicine is steadily finding its way into science. A recently conducted study on automated breast cancer detection using artificial intelligence establishes the basis for a future review in clinical studies.
Purpose
The Mayo Clinic Biobank was established to provide a large group of patients from which comparison groups (ie, controls) could be selected for case–control studies, to create a prospective cohort with sufficient power for common outcomes and to support electronic health record (EHR) studies.
Participants
A total of 56 862 participants enrolled (21% response rate) into the Mayo Clinic Biobank from Rochester, Minnesota (77%, n=43 836), Jacksonville, Florida (18%, n=10 368) and La Crosse, Wisconsin (5%, n=2658). Participants were all Mayo Clinic patients, 18 years of age or older and US residents.
Findings to date
Overall, 43% of participants were 65 years of age or older and female participants were more frequent (59%) than males at all sites. Most participants resided in the Upper Midwest regions of the USA (Minnesota, Iowa, Illinois or Wisconsin), Florida or Georgia. Self-reported race among Biobank participants was 90% white. Here we provide examples of the types of studies that have successfully utilised the resource, including (1) investigations of the population itself, (2) provision of controls for case–control studies, (3) genotype-driven research, (4) EHR-based research and (5) prospective recruitment to other studies. Over 270 projects have been approved to date to access Biobank data and/or samples; over 200 000 sample aliquots have been approved for distribution.
Future plans
The data and samples in the Mayo Clinic Biobank can be used for various types of epidemiological and clinical studies, especially in the setting of case–control studies for which the Biobank samples serve as control samples. We are planning cohort studies with additional follow-up and acquisition of genetic information on a large scale.
Most patients with Turner Syndrome (TS) need hormone replacement therapy because of hypergonadotropic hypogonadism; individual outcomes, however, are highly variable. Our objective was to assess the influence of five estrogen receptor 1 gene ( ESR1 ) polymorphisms (rs543650, rs1038304, rs2046210, rs2234693 and rs9340799) on adult height, breast development, uterine volume and bone mineral density (BMD). We studied 91 TS patients from a tertiary hospital using adult estrogen dose. In our group, ESR1 rs2234693 was associated with femoral neck and total hip BMD, and it accounted for around 10% of BMD variability in both sites (P-value<0.01). Patients homozygous for C allele in this polymorphism had significantly lower femoral neck BMD (0.699 ± 0.065g/cm2 vs. 0.822 ± 0.113g/cm2, P-value=0.008) and total hip BMD (0.777 ± 0.118g/cm2 vs. 0.903 ± 0.098g/cm2, P-value=0.009) than patients homozygous for T allele. The other four ESR1 polymorphisms were not able to predict any of the above estrogen therapy outcomes in an isolated manner. Patients homozygous for the haplotype GCG formed by polymorphisms rs543650, rs2234693 and rs9340799 had an even more significantly lower femoral neck BMD (0.666 ± 0.049 vs. 0.820 ± 0.105g/cm2, P-value=0.0047) and total hip BMD (0.752 ± 0.093 vs. 0.908 ±0.097g/cm2, P-value=0.0029) than patients homozygous for haplotypes with a T allele in rs2234693. In conclusion, homozygosity for C allele in ESR1 rs2234693 and/or for GCG haplotype appears to be associated with lower femoral neck and total hip BMD. We believe that the identification of polymorphisms related to estrogen outcomes may contribute to individualization of treatment in TS.
The further development of therapies for women with early breast cancer is progressing far more slowly than in the case of patients with advanced breast cancer and is additionally delayed compared to developments in metastatic breast cancer. Nonetheless, significant advancements have been able to be recorded recently. This review summarises the latest developments in view of the most recent publications and professional conferences. For hormone-receptor-positive patients, new aspects for the duration of antihormone therapy and with regard to the benefits of multigene tests have been published. In the case of HER2-positive patients, the value of post-neoadjuvant therapy and de-escalation of the therapy is discussed. In patients with triple-negative breast cancer, there is a question of whether the knowledge of the biological background of a homologous recombination deficiency (HRD) helps develop new therapies for this subtype. In particular the “use” of a BRCA1/2 mutation or the biological characteristic HRD as a potential motive for therapy plays a role here in specifying the significance of platinum therapy and therapy with PARP inhibitors.
Background:
Studies have identified that the telomerase reverse transcriptase (TERT) gene polymorphism rs10069690 (C>T) is associated with cancer risk, but the results remain inconclusive.
Methods:
To provide a more precise estimation of the relationship, we performed a meta-analysis of 45 published studies including 329,035 cases and 730,940 controls. We conducted a search in PubMed, Google Scholar and Web of Science to select studies on the association between rs10069690 and cancer risk. Stratification by ethnicity, cancer type, cancers' classification, source of control, sample size, and genotype method was used to explore the source of heterogeneity. The pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were evaluated using random effects models. Sensitivity, publication bias, false-positive report probability (FPRP) and statistical power were also assessed.
Results:
The result demonstrated that rs10069690 was significantly associated with an increased risk of cancer overall (OR = 1.09, 95% CI: 1.06-1.12, p < .001) under the allele model. Stratification analysis revealed an increased cancer risk in subgroups of breast cancer, ovarian cancer, lung cancer, thyroid cancer, and renal cell carcinoma (RCC). However, a significantly decreased association was observed in pancreatic cancer in the European population (OR = 0.93,95% CI: 0.87-0.99, p = .031). In the subgroup analysis based on cancer type, no significant association was found in prostate cancer, leukemia, colorectal cancer and glioma.
Conclusions:
This meta-analysis suggested that the TERT rs10069690 polymorphism may be a risk factor for cancer, especially breast cancer, ovarian cancer, lung cancer, thyroid cancer, and RCC. Further functional studies are warranted to reveal the role of the polymorphism in carcinogenesis.
For many years, small but significant advancements have been made time and again in the prevention and treatment of early breast cancer. The so-called panel gene analyses are becoming more and more important in prevention, since the risk due to the tested genes is better understood and as a result, concepts for integration in health care can be developed. In the adjuvant situation, the first study in the so-called post-neoadjuvant situation was able to demonstrate a clear improvement in the prognosis with an absent pathological complete remission following trastuzumab or pertuzumab + trastuzumab. Additional studies with this post-neoadjuvant therapeutic concept are still being conducted at present. The CDK4/6 inhibitors which had shown a significant improvement in progression-free survival in a metastatic situation are currently being tested in the adjuvant situation in large therapeutic studies. These and other new data for the treatment or prevention of primary breast cancer are presented in this review against the backdrop of current studies.
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