A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age

Genetic Variants and Haplotype Structures in the CASC Gene Family to Predict Cancer Risk: A Bioinformatics Study

Background and Aims

The cancer susceptibility (CASC) gene family of long noncoding RNAs (lncRNAs) plays an important role in cancer. The aim of this study was to identify genetic variants and haplotype structures of CASC genes associated with cancer risk.

Methods

Genome-wide association studies (GWAS) significant variants (p ≤ 5 × 10-8) on CASC family genes were identified from the GWAS Catalog-EMBL-EBI, and then cancer-associated variants on CASC genes were extracted. These variants were functionally analyzed, including lncRNA:miRNA binding sites, Regulomedb scores, and eQTL. The 1000 Genome Project genotyping data Phase III were used to identify haplotypic blocks. Finally, the genes associated with them were examined for expression and gene-gene correlation analyses using OncoDB.

Results

There were six haplotypic blocks in four genes. The GC, TA, and AGAC haplotypes are located in the CASC8 gene and increase the risk of prostate cancer, breast cancer, and colorectal cancer, respectively. The CA haplotype in the CASC15 gene increases the risk of neuroblastoma, AA haplotype in the CASC16 gene increases the risk of breast cancer, and ACGATG haplotype in the CASC17 gene increases the risk of prostate cancer (p ≤ 5 × 10-8). Their genes are interrelated and their expression is increased in these cancers. The rs2294214 is associated with skin cancer and has positive effects on five CASC15:miRNA binding sites. The rs3803662 is located in CASC16:miRNA binding sites, which has positive effects on hsa-miR-4475 and hsa-miR-7845-5p and negative effects on hsa-miR-4524a-3p and hsa-miR-4524b-3p.

Conclusion

These haplotypic structures and lncRNA:miRNA:SNP interactions on CASC family lncRNAs reveal novel genetic associations between CASC genes and various cancers.

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

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

Biomimetic Synthesis and Chemical Proteomics Reveal the Mechanism of Action and Functional Targets of Phloroglucinol Meroterpenoids

Natural products perennially serve as prolific sources of drug leads and chemical probes, fueling the development of numerous therapeutics. Despite their scarcity, natural products that modulate protein function through covalent interactions with lysine residues hold immense potential to unlock new therapeutic interventions and advance our understanding of the biological processes governed by these modifications. Phloroglucinol meroterpenoids constitute one of the most expansive classes of natural products, displaying a plethora of biological activities. However, their mechanism of action and cellular targets have, until now, remained elusive. In this study, we detail the concise biomimetic synthesis, computational mechanistic insights, physicochemical attributes, kinetic parameters, molecular mechanism of action, and functional cellular targets of several phloroglucinol meroterpenoids. We harness synthetic clickable analogues of natural products to probe their disparate proteome-wide reactivity and subcellular localization through in-gel fluorescence scanning and cell imaging. By implementing sample multiplexing and a redesigned lysine-targeting probe, we streamline a quantitative activity-based protein profiling, enabling the direct mapping of global reactivity and ligandability of proteinaceous lysines in human cells. Leveraging this framework, we identify numerous lysine-meroterpenoid interactions in breast cancer cells at tractable protein sites across diverse structural and functional classes, including those historically deemed undruggable. We validate that phloroglucinol meroterpenoids perturb biochemical functions through stereoselective and site-specific modification of lysines in proteins vital for breast cancer metabolism, including lipid signaling, mitochondrial respiration, and glycolysis. These findings underscore the broad potential of phloroglucinol meroterpenoids for targeting functional lysines in the human proteome.

Investigation of common genetic risk factors between thyroid traits and breast cancer

Breast cancer (BC) risk is suspected to be linked to thyroid disorders, however observational studies exploring the association between BC and thyroid disorders gave conflicting results. We proposed an alternative approach by investigating the shared genetic risk factors between BC and several thyroid traits. We report a positive genetic correlation between BC and thyroxine (FT4) levels (corr = 0.13, p-value = 2.0 × 10-4) and a negative genetic correlation between BC and thyroid-stimulating hormone (TSH) levels (corr = -0.09, p-value = 0.03). These associations are more striking when restricting the analysis to estrogen receptor-positive BC. Moreover, the polygenic risk scores (PRS) for FT4 and hyperthyroidism are positively associated to BC risk (OR = 1.07, 95%CI: 1.00-1.13, p-value = 2.8 × 10-2 and OR = 1.04, 95%CI: 1.00-1.08, p-value = 3.8 × 10-2, respectively), while the PRS for TSH is inversely associated to BC risk (OR = 0.93, 95%CI: 0.89-0.97, p-value = 2.0 × 10-3). Using the PLACO method, we detected 49 loci associated to both BC and thyroid traits (p-value < 5 × 10-8), in the vicinity of 130 genes. An additional colocalization and gene-set enrichment analyses showed a convincing causal role for a known pleiotropic locus at 2q35 and revealed an additional one at 8q22.1 associated to both BC and thyroid cancer. We also found two new pleiotropic loci at 14q32.33 and 17q21.31 that were associated to both TSH levels and BC risk. Enrichment analyses and evidence of regulatory signals also highlighted brain tissues and immune system as candidates for obtaining associations between BC and TSH levels. Overall, our study sheds light on the complex interplay between BC and thyroid traits and provides evidence of shared genetic risk between those conditions.

Genetic and non-genetic risk factors for early-onset pancreatic cancer

BACKGROUND

Early-onset pancreatic cancer (EOPC) represents 5-10% of all pancreatic ductal adenocarcinoma (PDAC) cases, and the etiology of this form is poorly understood. It is not clear if established PDAC risk factors have the same relevance for younger patients. This study aims to identify genetic and non-genetic risk factors specific to EOPC.

METHODS

A genome-wide association study was performed, analysing 912 EOPC cases and 10 222 controls, divided into discovery and replication phases. Furthermore, the associations between a polygenic risk score (PRS), smoking, alcohol consumption, type 2 diabetes and PDAC risk were also assessed.

RESULTS

Six novel SNPs were associated with EOPC risk in the discovery phase, but not in the replication phase. The PRS, smoking, and diabetes affected EOPC risk. The OR comparing current smokers to never-smokers was 2.92 (95% CI 1.69-5.04, P = 1.44 × 10-4). For diabetes, the corresponding OR was 14.95 (95% CI 3.41-65.50, P = 3.58 × 10-4).

CONCLUSION

In conclusion, we did not identify novel genetic variants associated specifically with EOPC, and we found that established PDAC risk variants do not have a strong age-dependent effect. Furthermore, we add to the evidence pointing to the role of smoking and diabetes in EOPC.

Development and testing of a polygenic risk score for breast cancer aggressiveness

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

What Is Known about Breast Cancer in Young Women?

Breast cancer (BC) is the second leading cause of cancer-related death in women under the age of 40 years worldwide. In addition, the incidence of breast cancer in young women (BCYW) has been rising. Young women are not the focus of screening programs and BC in younger women tends to be diagnosed in more advanced stages. Such patients have worse clinical outcomes and treatment complications compared to older patients. BCYW has been associated with distinct tumour biology that confers a worse prognosis, including poor tumour differentiation, increased Ki-67 expression, and more hormone-receptor negative tumours compared to women >50 years of age. Pathogenic variants in cancer predisposition genes such as BRCA1/2 are more common in early-onset BC compared to late-onset BC. Despite all these differences, BCYW remains poorly understood with a gap in research regarding the risk factors, diagnosis, prognosis, and treatment. Age-specific clinical characteristics or outcomes data for young women are lacking, and most of the standard treatments used in this subpopulation currently are derived from older patients. More age-specific clinical data and treatment options are required. In this review, we discuss the epidemiology, clinicopathologic characteristics, outcomes, treatments, and special considerations of breast cancer in young women. We also underline future directions and highlight areas that require more attention in future studies.

Association of PFKM gene polymorphisms and susceptibility to cryptorchidism in a Chinese Han population

BACKGROUND

Cryptorchidism is one of the most common congenital anomalies in newborn boys. There are various risk factors that have been verified to have relationship with cryptorchidism, including exogenous and genetic, but the pathogenesis of cryptorchidism remains unclear. PFKM gene is a critical gene encodes for a regulatory enzyme, which limits the rate in the pathway of glycolysis. We assumed that cryptorchidism risk may associated with PFKM gene single-nucleotide polymorphisms (SNPs). Thus we selected three tag SNPs in the PFKM gene and aimed to investigate the possible association between PFKM gene polymorphisms and cryptorchidism risk.

METHODS

The SNPs were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. 140 cases and 227 controls were enrolled in this study, including 105 unilateral cryptorchidism and 35 bilateral cases. The testis position was decided by the higher one in bilateral cases.

RESULTS

The frequency of allele G of SNP rs2228500 is increased in cryptorchidism patients compared to that in controls (p < 0.05). Genotypic frequencies of rs2228500 are associated with the susceptibility of cryptorchidism in the codominant model (p < 0.05). And compared with G/G genotype in the dominant model, notable decreased frequencies of A carriers (A/G-A/A genotypes) were observed in cryptorchidism patients (p = 0.0069, OR = 1.80, 95% CI  1.17-2.75).

CONCLUSIONS

This research first revealed that PFKM gene polymorphisms were associated with cryptorchidism in a Chinese Han population. We have offered primary evidence that the G allele and the G/G genotype of rs2228500 SNP in the PFKM gene are more frequent in patients with cryptorchidism than healthy controls.

PFKM inhibits doxorubicin-induced cardiotoxicity by enhancing oxidative phosphorylation and glycolysis

Heart failure (HF) is a global pandemic which affects about 26 million people. PFKM (Phosphofructokinase, Muscle), catalyzing the phosphorylation of fructose-6-phosphate, plays a very important role in cardiovascular diseases. However, the effect of PFKM in glycolysis and HF remains to be elucidated. H9c2 rat cardiomyocyte cells were treated with doxorubicin (DOX) to establish injury models, and the cell viability, apoptosis and glycolysis were measured. Quantitative reverse transcription-polymerase chain reaction (RT-PCR) and immunoblotting were used for gene expression. DOX treatment significantly inhibited PFKM expression in H9c2 cells. Overexpression of PFKM inhibited DOX-induced cell apoptosis and DOX-decreased glycolysis and oxidative phosphorylation (OXPHOS), while silencing PFKM promoted cell apoptosis and inhibited glycolysis and OXPHOS in H9c2 cells. Moreover, PFKM regulated DOX-mediated cell viability and apoptosis through glycolysis pathway. Mechanism study showed that histone deacetylase 1 (HDAC1) inhibited H3K27ac-induced transcription of PFKM in DOX-treated cells and regulated glycolysis. PFKM could inhibit DOX-induced cardiotoxicity by enhancing OXPHOS and glycolysis, which might benefit us in developing novel therapeutics for prevention or treatment of HF.

HOXA1, a breast cancer oncogene

More than 25 years ago, the first literature records mentioned HOXA1 expression in human breast cancer. A few years later, HOXA1 was confirmed as a proper oncogene in mammary tissue. In the following two decades, molecular data about the mode of action of the HOXA1 protein, the factors contributing to activate and maintain HOXA1 gene expression and the identity of its target genes have accumulated and provide a wider view on the association of this transcription factor to breast oncogenesis. Large-scale transcriptomic data gathered from wide cohorts of patients further allowed refining the relationship between breast cancer type and HOXA1 expression. Several recent reports have reviewed the connection between cancer hallmarks and the biology of HOX genes in general. Here we take HOXA1 as a paradigm and propose an extensive overview of the molecular data centered on this oncoprotein, from what its expression modulators, to the interactors contributing to its oncogenic activities, and to the pathways and genes it controls. The data converge to an intricate picture that answers questions on the multi-modality of its oncogene activities, point towards better understanding of breast cancer aetiology and thereby provides an appraisal for treatment opportunities.

Targeting epidermal growth factor receptor in paclitaxel-resistant human breast and lung cancer cells with upregulated glucose-6-phosphate dehydrogenase

BACKGROUND

Chemoresistance is a major obstacle to the successful treatment of triple-negative breast cancer (TNBC) and non-small-cell lung cancer (NSCLC). Therapeutic strategies to overcome chemoresistance are necessary to improve the prognosis of patients with these cancers.

METHODS

Paclitaxel-resistant TNBC and NSCLC sublines were generated through continuous paclitaxel treatment over 6 months. The mechanistic investigation was conducted using MTT assay, LC/MS-based metabolite analysis, flow cytometry, western blot analysis, real-time PCR and tumour xenograft experiments.

RESULTS

Glucose-6-phosphate dehydrogenase (G6PD) expression along with an increase in 3-phosphoglycerates and ribulose-5-phosphate production was upregulated in paclitaxel-resistant cells. Blockade of G6PD decreased viability of paclitaxel-resistant cells in vitro and the growth of paclitaxel-resistant MDA/R xenograft tumours in vivo. Mechanistically, activation of the epidermal growth factor receptor (EGFR)/Akt pathway mediates G6PD expression and G6PD-induced cell survival. Blockade of the EGFR pathway inhibited G6PD expression and sensitised those paclitaxel-resistant cells to paclitaxel treatment in vitro and in vivo. Analysis of publicly available datasets revealed an association between G6PD and unfavourable clinical outcomes in patients with breast or lung cancer.

CONCLUSIONS

EGFR signaling-mediated G6PD expression plays a pivotal role in paclitaxel resistance, highlighting the potential of targeting EGFR to overcome paclitaxel resistance in TNBC and NSCLC cells overexpressing G6PD.

Expression of HK2, PKM2, and PFKM Is Associated with Metastasis and Late Disease Onset in Breast Cancer Patients

The reprogramming of energy metabolism is one of the hallmarks of cancer and is crucial for tumor progression. Altered aerobic glycolysis is a well-known characteristic of cancer cell metabolism. In the present study, the expression profiles of key metabolic genes (HK2, PFKM, and PKM2) were assessed in the breast cancer cohort of Pakistan using quantitative polymerase chain reaction (qPCR) and IHC. Expression patterns were correlated with molecular subtypes and clinical parameters in the patients. A significant upregulation of key glycolytic genes was observed in tumor samples in comparison to their adjacent controls (p < 0.0001). The expression of the studied glycolytic genes was significantly increased in late clinical stages, positive nodal involvement, and distant metastasis (p < 0.05). HK2 and PKM2 were found to be upregulated in luminal B, whereas PFKM was overexpressed in the luminal A subtype of breast cancer. The genes were positively correlated with the proliferation marker Ki67 (p < 0.001). Moreover, moderate positive linear correlations between HK2 and PKM2 (r = 0.476), HK2 and PFKM (r = 0.473), and PKM2 and PFKM (r = 0.501) were also observed (p < 0.01). These findings validate that the key regulatory genes in glycolysis can serve as potential biomarkers and/or molecular targets for breast cancer management. However, the clinical significance of these molecules needs to be further validated through in vitro and in vivo experiments.

Comprehensive Analysis of the Glycolysis-Related Gene Prognostic Signature and Immune Infiltration in Endometrial Cancer

Glucose metabolic reprogramming and immune imbalance play important roles in the progression of cancers. The purpose of this study is to develop a glycolysis-related prognostic signature for endometrial cancer (EC) and analyze its relationship with immune function. The mRNA expression profiling of the glycolysis-related genes and clinical data of EC patients were downloaded from The Cancer Genome Atlas (TCGA). We identified a glycolysis-related gene prognostic signature for predicting the prognosis of EC by using The Least Absolute Shrinkage and Selection Operator (LASSO) regression and found the patients in the high-risk group had worse survival prognosis. Multivariate Cox regression analysis showed that the gene signature was an independent prognostic factor for EC. The ROC curve confirmed the accuracy of the prognostic signature (AUC = 0.730). Then, we constructed a nomogram to predict the 1–5 years survival rate of EC patients. The association between the gene signature and immune function was analyzed based on the “ESTIMATE” and “CIBERSORT” algorithm, which showed the immune and ESTIMATE scores of patients in the high-risk group were lower, while the low immune and ESTIMATE scores were associated with a worse prognosis of patients. The imbalance of immune cells was also found in the high-risk group. Further, the protein of CDK1, a gene in the signature, was found to be closely related to prognosis of EC and inhibition of CDK1 could inhibit migration and promote apoptosis of EC cells. This study reveals a link between glycolysis-related gene signature and immunity, and provides personalized therapeutic targets for EC.

Phosphoproteomic Analysis of Breast Cancer-Derived Small Extracellular Vesicles Reveals Disease-Specific Phosphorylated Enzymes

Small membrane-derived extracellular vesicles have been proposed as participating in several cancer diseases, including breast cancer (BC). We performed a phosphoproteomic analysis of breast cancer-derived small extracellular vesicles (sEVs) to provide insight into the molecular and cellular regulatory mechanisms important for breast cancer tumor progression and metastasis. We examined three cell line models for breast cancer: MCF10A (non-malignant), MCF7 (estrogen and progesterone receptor-positive, metastatic), and MDA-MB-231 (triple-negative, highly metastatic). To obtain a comprehensive overview of the sEV phosphoproteome derived from each cell line, effective phosphopeptide enrichment techniques IMAC and TiO2, followed by LC-MS/MS, were performed. The phosphoproteome was profiled to a depth of 2003 phosphopeptides, of which 207, 854, and 1335 were identified in MCF10A, MCF7, and MDA-MB-231 cell lines, respectively. Furthermore, 2450 phosphorylation sites were mapped to 855 distinct proteins, covering a wide range of functions. The identified proteins are associated with several diseases, mostly related to cancer. Among the phosphoproteins, we validated four enzymes associated with cancer and present only in sEVs isolated from MCF7 and MDA-MB-231 cell lines: ATP citrate lyase (ACLY), phosphofructokinase-M (PFKM), sirtuin-1 (SIRT1), and sirtuin-6 (SIRT6). With the exception of PFKM, the specific activity of these enzymes was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study demonstrates that sEVs contain functional metabolic enzymes that could be further explored for their potential use in early BC diagnostic and therapeutic applications.

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we developed Transcriptome-Integrated Genetic Association Resource V2 (TIGAR-V2), which directly reads Variant Call Format (VCF) files, enables parallel computation, and reduces up to 90% of computation cost (mainly due to loading genotype data) compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. We trained gene expression prediction models by DPR for 49 tissues using Genotype-Tissue Expression (GTEx) V8 by TIGAR-V2 and illustrated the usefulness of these Bayesian cis-expression quantitative trait locus (eQTL) weights through TWASs of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes, respectively, for breast and ovarian cancer, most of which are either known or near previously identified GWAS (∼95%) or TWAS (∼40%) risk genes and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWASs can provide biological insight into the transcriptional regulation of complex diseases. The TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and linkage disequilibrium (LD) information from GTEx V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

MicroRNA-383-5p Regulates Oxidative Stress in Mice with Acute Myocardial Infarction through the AMPK Signaling Pathway via PFKM

Objective

The purpose of this study is to explore the regulating role of microRNA-383-5p (miR-383-5p) in oxidative stress after acute myocardial infarction (AMI) through AMPK pathway via phosphofructokinase muscle-type (PFKM).

Methods

We established the AMI model, and the model mice were injected with miR-383-5p agomir to study the effect of miR-383-5p in AMPK signaling pathways. The target gene for miR-383-5p was reported to be PFKM, so we hypothesized that overexpression of miR-383-5p inhibits activation of the AMPK signaling pathway.

Results

In this research, we found that overexpression of miR-383-5p decreases myocardial oxidative stress, myocardial apoptosis, the expression level of PFKM malondialdehyde (MDA), and reactive oxygen species (ROS) in the myocardial tissues after AMI, and finally, AMI-induced cardiac systolic and diastolic function could be improved.

Conclusion

This study demonstrated that miR-383-5p could reduce the oxidative stress after AMI through AMPK signaling pathway by targeting PFKM.

Effect of lncRNA XLOC_005950 knockout by CRISPR/Cas9 gene editing on energy metabolism and proliferation in osteosarcoma MG63 cells mediated by hsa-miR-542-3p

Cancer cells use glucose via glycolysis to maintain tumor cell proliferation. However, the effect of long non-coding RNAs (lncRNAs) on glycolysis in osteosarcoma (OS) cells remains unclear. The present study aimed to investigate the involvement of the lncRNA XLOC_005950/hsa-microRNA (miR)-542-3p/phosphofructokinase, muscle (PFKM) axis in the regulation of glucose metabolism, cell proliferation and apoptosis in the progression of OS. lncRNA XLOC_005950, hsa-miR-542-3p and PFKM expression in OS tissues and cells was detected via reverse transcription-quantitative PCR analysis. CRISPR/Cas9 gene editing was used to knockout lncRNA XLOC_005950 expression in MG63 cells. Cell Counting Kit-8 assay, flow cytometry, PFKM activity, and glucose and lactic acid content determination were performed to assess the effects of lncRNA XLOC_005950 knockout and overexpression of hsa-miR-542-3p on the phenotypes of OS cells. The dual-luciferase reporter assay was performed to confirm the targeting associations between lncRNA XLOC_005950, hsa-miR-542-3p and PFKM. The results demonstrated that lncRNA XLOC_005950 expression was upregulated in OS tissues and cells. Functional experiments indicated that lncRNA XLOC_005950 knockout decreased PFKM activity, the intracellular glucose and lactic acid content, and cell proliferation, while increasing apoptosis of OS cells. Furthermore, lncRNA XLOC_005950 knockout upregulated hsa-miR-542-3p expression and downregulated PFKM expression. Overexpression of hsa-miR-542-3p suppressed PFKM expression. Furthermore, lncRNA XLOC_005950, as the molecular sponge of miR-542-3p in OS, modulated the downstream target gene, PFKM. Taken together, the results of the present study suggest that lncRNA XLOC_005950 knockout may inhibit the progression of OS via hsa-miR-542-3p-mediated regulation of PFKM expression.

Obesity in early onset breast cancer in African American patients

Obesity is a modifiable risk factor in breast cancer patients and is predictive of disease outcomes in early-onset breast cancer survivors. The purpose of this review is to summarize the current evidence in the association between early-onset breast cancer and obesity, specifically in African-American women. Reviewing the molecular mechanisms and social determinants of disease in this population can provide a foundation for future interventions in prevention, detection, and treatment aiming at improving outcomes for young breast cancer patients.

The Unique Biology behind the Early Onset of Breast Cancer

Breast cancer commonly affects women of older age; however, in developing countries, up to 20% of breast cancer cases present in young women (younger than 40 years as defined by oncology literature). Breast cancer in young women is often defined to be aggressive in nature, usually of high histological grade at the time of diagnosis and negative for endocrine receptors with poor overall survival rate. Several researchers have attributed this aggressive nature to a hidden unique biology. However, findings in this aspect remain controversial. Thus, in this article, we aimed to review published work addressing somatic mutations, chromosome copy number variants, single nucleotide polymorphisms, differential gene expression, microRNAs and gene methylation profile of early-onset breast cancer, as well as its altered pathways resulting from those aberrations. Distinct biology behind early-onset of breast cancer was clear among estrogen receptor-positive and sporadic cases. However, further research is needed to determine and validate specific novel markers, which may help in customizing therapy for this group of patients.

Feature selection and classification approaches in gene expression of breast cancer

<abstract> <p>DNA microarray technology with biological data-set can monitor the expression levels of thousands of genes simultaneously. Microarray data analysis is important in phenotype classification of diseases. In this work, the computational part basically predicts the tendency towards mortality using different classification techniques by identifying features from the high dimensional dataset. We have analyzed the breast cancer transcriptional genomic data of 1554 transcripts captured over from 272 samples. This work presents effective methods for gene classification using Logistic Regression (LR), Random Forest (RF), Decision Tree (DT) and constructs a classifier with an upgraded rate of accuracy than all features together. The performance of these underlying methods are also compared with dimension reduction method, namely, Principal Component Analysis (PCA). The methods of feature reduction with RF, LR and decision tree (DT) provide better performance than PCA. It is observed that both techniques LR and RF identify TYMP, ERS1, C-MYB and TUBA1a genes. But some features corresponding to the genes such as ARID4B, DNMT3A, TOX3, RGS17 and PNLIP are uniquely pointed out by LR method which are leading to a significant role in breast cancer. The simulation is based on <italic>R</italic>-software.</p> </abstract>

Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer

BACKGROUND

Cervical cancer (CC) is one of the most common gynaecological cancers. The gene signature is believed to be reliable for predicting cancer patient survival. However, there is no relevant study on the relationship between the glycolysis-related gene (GRG) signature and overall survival (OS) of patients with CC.

METHODS

We extracted the mRNA expression profiles of 306 tumour and 13 normal tissues from the University of California Santa Cruz (UCSC) Database. Then, we screened out differentially expressed glycolysis-related genes (DEGRGs) among these mRNAs. All patients were randomly divided into training cohort and validation cohort according to the ratio of 7: 3. Next, univariate and multivariate Cox regression analyses were carried out to select the GRG with predictive ability for the prognosis of the training cohort. Additionally, risk score model was constructed and validated it in the validation cohort.

RESULTS

Six mRNAs were obtained that were associated with patient survival. The filtered mRNAs were classified into the protective type (GOT1) and the risk type (HSPA5, ANGPTL4, PFKM, IER3 and PFKFB4). Additionally, by constructing the prognostic risk score model, we found that the OS of the high-risk group was notably poorer, which showed good predictive ability both in training cohort and validation cohort. And the six-gene signature is a prognostic indicator independent of clinicopathological features. Through the verification of PCR, the results showed that compared with the normal cervial tissuses, the expression level of six mRNAs were significantly higher in the CC tissue, which was consistent with our findings.

CONCLUSIONS

We constructed a glycolysis-related six-gene signature to predict the prognosis of patients with CC using bioinformatics methods. We provide a thorough comprehension of the effect of glycolysis in patients with CC and provide new targets and ideas for individualized treatment.

SiRNA targeting PFK1 inhibits proliferation and migration and enhances radiosensitivity by suppressing glycolysis in colorectal cancer

PURPOSE

This study explored the effects of phosphofructokinase-1 (PFK1) on the radiosensitivity of colorectal cancer (CRC) in vivo and in vitro and the underlying mechanisms.

METHODS

Tissue samples from 48 patients with rectal cancer who had received neoadjuvant radiotherapy followed by surgery were analyzed. The expression of PFK1 in tissue samples was semi-quantitated by immunohistochemistry, and its relationship with clinicopathological features was analyzed. The effects of PFK1 knockdown on the survival, apoptosis, migration, and radiosensitivity of CRC cells were evaluated. Glycolysis-related indicators were used to examine glycolytic activity. The effects of PFK1 on the radiosensitivity of CRC in vivo were assessed by measuring tumor formation in nude mice.

RESULTS

PFK1 was overexpressed in rectal cancer and was higher in radiation-resistant tumors than in radiation-sensitive tumors. SiRNA-induced PFK1 silencing increased apoptosis and inhibited migration and proliferation of CRC cells. Knockdown of PFK1 made the CRC cells sensitive to ionizing radiation in vivo. Oligomycin partially restored the expression of PFK1, enhanced glycolysis, and reversed the enhanced radiosensitivity of CRC cells induced by siRNA-PFK1. Downregulation of PFK1 combined with irradiation inhibited growth of nude mice xenografts, which was related to an increase in apoptosis.

CONCLUSIONS

Our study indicates that high expression of PFK1 is negatively correlated with radiosensitivity in CRC and likely accelerates the proliferation and migration of CRC cells. Downregulation of PFK1 may enhance the radiosensitivity of CRC cells in vivo and in vitro by inhibiting glycolysis.

A genetic variant in the promoter of CD46 is associated with the risk and prognosis of hepatocellular carcinoma

CD46 (also known as membrane cofactor protein), which is a member of the membrane-bound complement regulatory protein family, has been reported to cause cancer cells to escape complement-dependent cytotoxicity. However, the association between CD46 polymorphisms and the risk of hepatocellular carcinoma (HCC) has not been investigated. This two-stage association study was conducted to assess the relationship between the tagging single nucleotide polymorphisms (tagSNPs) of CD46 and HCC risk and prognosis. A series of functional analyses were performed to study the underlying mechanisms. Among the eight tagSNPs, rs2796267 (P = .003) and rs2796268 (P = .011) were found to modify HCC risk in the discovery set. Only rs2796267 (P < .0001) was confirmed to be associated with HCC susceptibility in the validation set. Compared with the wild-type AA genotype, the GG genotype significantly increased the HCC risk (adjusted odds ratio [OR] = 2.03; 95% confidence interval [CI], 1.34-3.08; P = .001). Moreover, subgroups analysis suggested a positive correlation among male and younger patients, especially among drinkers, smokers, and hepatitis B surface antigen-positive individuals. In functional analyses, we found that the rs2796267 G allele in the promoter region of CD46 could increase the expression of CD46 by affecting the binding affinity of STAT5a. Furthermore, Cox regression analysis revealed that the rs2796267 AG/GG genotype was significantly associated with worse prognosis of resected patients with HCC (hazard ratio = 2.27; 95% CI, 1.27-4.05; P = .006). These results suggest that the CD46 rs2796267 polymorphism may contribute to susceptibility and prognosis of HCC by altering promoter activity.

Comprehensive Cohort Analysis of Mutational Spectrum in Early Onset Breast Cancer Patients

Early onset breast cancer (EOBC), diagnosed at age ~40 or younger, is associated with a poorer prognosis and higher mortality rate compared to breast cancer diagnosed at age 50 or older. EOBC poses a serious threat to public health and requires in-depth investigation. We studied a cohort comprising 90 Taiwanese female patients, aiming to unravel the underlying mechanisms of EOBC etiopathogenesis. Sequence data generated by whole-exome sequencing (WES) and whole-genome sequencing (WGS) from white blood cell (WBC)-tumor pairs were analyzed to identify somatic missense mutations, copy number variations (CNVs) and germline missense mutations. Similar to regular breast cancer, the key somatic mutation-susceptibility genes of EOBC include TP53 (40% prevalence), PIK3CA (37%), GATA3 (17%) and KMT2C (17%), which are frequently reported in breast cancer; however, the structural protein-coding genes MUC17 (19%), FLG (16%) and NEBL (11%) show a significantly higher prevalence in EOBC. Furthermore, the top 2 genes harboring EOBC germline mutations, MUC16 (19%) and KRT18 (19%), encode structural proteins. Compared to conventional breast cancer, an unexpectedly higher number of EOBC susceptibility genes encode structural proteins. We suspect that mutations in structural proteins may increase physical permeability to environmental hormones and carcinogens and cause breast cancer to occur at a young age.

DOT: Gene-set analysis by combining decorrelated association statistics

Historically, the majority of statistical association methods have been designed assuming availability of SNP-level information. However, modern genetic and sequencing data present new challenges to access and sharing of genotype-phenotype datasets, including cost of management, difficulties in consolidation of records across research groups, etc. These issues make methods based on SNP-level summary statistics particularly appealing. The most common form of combining statistics is a sum of SNP-level squared scores, possibly weighted, as in burden tests for rare variants. The overall significance of the resulting statistic is evaluated using its distribution under the null hypothesis. Here, we demonstrate that this basic approach can be substantially improved by decorrelating scores prior to their addition, resulting in remarkable power gains in situations that are most commonly encountered in practice; namely, under heterogeneity of effect sizes and diversity between pairwise LD. In these situations, the power of the traditional test, based on the added squared scores, quickly reaches a ceiling, as the number of variants increases. Thus, the traditional approach does not benefit from information potentially contained in any additional SNPs, while our decorrelation by orthogonal transformation (DOT) method yields steady gain in power. We present theoretical and computational analyses of both approaches, and reveal causes behind sometimes dramatic difference in their respective powers. We showcase DOT by analyzing breast cancer and cleft lip data, in which our method strengthened levels of previously reported associations and implied the possibility of multiple new alleles that jointly confer disease risk.

Interactions between a Polygenic Risk Score and Non-genetic Risk Factors in Young-Onset Breast Cancer

Most gene-environmental studies have focused on breast cancers generally, the preponderance of which occur after age 50. Young-onset breast cancers (YOBC) tend to be aggressive and may be etiologically different. The goal of this analysis was to assess interactions between an established 77-SNP polygenic risk score (PRS) and non-genetic risk factors for YOBC. We constructed the PRS using a family-based study of 1,291 women diagnosed with breast cancer before age 50 and their parents and unaffected sisters. We used conditional logistic regression to analyze interactions between the PRS and 14 established risk factors. In further analyses we assessed the same interactions, but for invasive cancer, estrogen receptor (ER) positive cancer and with broader inclusion of racial/ethnic groups. Results showed a decreased association between the PRS and YOBC risk for women who had ever used hormonal birth control (odds ratio [OR] = 2.20 versus 3.89) and a stronger association between the PRS and YOBC risk in pre-menopausal women (OR = 2.46 versus 1.23). Restricting the analysis to ER+ cancers or invasive cancers or using samples from all ethnic groups produced similar results. In conclusion, the PRS may interact with hormonal birth control use and with menopausal status on risk of YOBC.

MICA-129 Met/Val polymorphism could be a genetic biomarker for Familial Breast Cancer in the Tunisian population

Identification of candidate genes associated with susceptibility of breast cancer can have a significant impact at a cancer management national healthcare systems level, making genetic testing more affordable and cost-effective. We have previously shown that the major histocompatibility complex class I-related chain A (MICA) was related to breast cancer and plays an important role in modulating immune response mechanisms through NKG2D receptor activation. Compared to our previous study, in this work, we recruited a new cohort composed of 354 unrelated Tunisian women affected by breast cancer and 380 age-matched women as controls, all genotyped for MICA-129 Met/Val (rs 1051792). Subsequently, we exanimated the distribution of this polymorphism in ten families. As a result, an association was found between the Val allele and Val/Val genotype and the risk of breast cancer (p = 2.5 × 10^-15 ; OR = 2.40; p = 6.5 × 10^-13 ; OR = 3.03, respectively). Stratified analysis with age and family history of cancer revealed an association between the Val/Val genotype and younger patients <40 years (p = .003; OR = 2.03). Among those patients having a family history of cancer, 68% had a Val/Val genotype (p = .02; OR = 1.82). In the family study, an analyse of pedigrees revealed that the majority of families showed the development of breast cancer at a young age. Moreover, all patients diagnosed with early-onset breast cancer had a Val/Val genotype. Our results lead us to propose that this polymorphism may be an inherited genetic biomarker contributing to an increased breast cancer risk in Tunisian women.

Recursive Feature Elimination by Sensitivity Testing

There is great interest in methods to improve human insight into trained non-linear models. Leading approaches include producing a ranking of the most relevant features, a non-trivial task for non-linear models. We show theoretically and empirically the benefit of a novel version of recursive feature elimination (RFE) as often used with SVMs; the key idea is a simple twist on the kinds of sensitivity testing employed in computational learning theory with membership queries (e.g., [1]). With membership queries, one can check whether changing the value of a feature in an example changes the label. In the real-world, we usually cannot get answers to such queries, so our approach instead makes these queries to a trained (imperfect) non-linear model. Because SVMs are widely used in bioinformatics, our empirical results use a real-world cancer genomics problem; because ground truth is not known for this task, we discuss the potential insights provided. We also evaluate on synthetic data where ground truth is known.

Identification of two novel breast cancer loci through large-scale genome-wide association study in the Japanese population

Genome-wide association studies (GWAS) have successfully identified about 70 genomic loci associated with breast cancer. Owing to the complexity of linkage disequilibrium and environmental exposures in different populations, it is essential to perform regional GWAS for better risk prediction. This study aimed to investigate the genetic architecture and to assess common genetic risk model of breast cancer with 6,669 breast cancer patients and 21,930 female controls in the Japanese population. This GWAS identified 11 genomic loci that surpass genome-wide significance threshold of P < 5.0 × 10⁻⁸ with nine previously reported loci and two novel loci that include rs9862599 on 3q13.11 (ALCAM) and rs75286142 on 21q22.12 (CLIC6-RUNX1). Validation study was carried out with 981 breast cancer cases and 1,394 controls from the Aichi Cancer Center. Pathway analyses of GWAS signals identified association of dopamine receptor medicated signaling and protein amino acid deacetylation with breast cancer. Weighted genetic risk score showed that individuals who were categorized in the highest risk group are approximately 3.7 times more likely to develop breast cancer compared to individuals in the lowest risk group. This well-powered GWAS is a representative study to identify SNPs that are associated with breast cancer in the Japanese population.

Association between mitochondrial genetic variation and breast cancer risk: The Multiethnic Cohort

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.

DNA Methylation Module Network-Based Prognosis and Molecular Typing of Cancer

Achieving cancer prognosis and molecular typing is critical for cancer treatment. Previous studies have identified some gene signatures for the prognosis and typing of cancer based on gene expression data. Some studies have shown that DNA methylation is associated with cancer development, progression, and metastasis. In addition, DNA methylation data are more stable than gene expression data in cancer prognosis. Therefore, in this work, we focused on DNA methylation data. Some prior researches have shown that gene modules are more reliable in cancer prognosis than are gene signatures and that gene modules are not isolated. However, few studies have considered cross-talk among the gene modules, which may allow some important gene modules for cancer to be overlooked. Therefore, we constructed a gene co-methylation network based on the DNA methylation data of cancer patients, and detected the gene modules in the co-methylation network. Then, by permutation testing, cross-talk between every two modules was identified; thus, the module network was generated. Next, the core gene modules in the module network of cancer were identified using the K-shell method, and these core gene modules were used as features to study the prognosis and molecular typing of cancer. Our method was applied in three types of cancer (breast invasive carcinoma, skin cutaneous melanoma, and uterine corpus endometrial carcinoma). Based on the core gene modules identified by the constructed DNA methylation module networks, we can distinguish not only the prognosis of cancer patients but also use them for molecular typing of cancer. These results indicated that our method has important application value for the diagnosis of cancer and may reveal potential carcinogenic mechanisms.

The CIMP-high phenotype is associated with energy metabolism alterations in colon adenocarcinoma

BACKGROUND

CpG island methylator phenotype (CIMP) is found in 15-20% of malignant colorectal tumors and is characterized by strong CpG hypermethylation over the genome. The molecular mechanisms of this phenomenon are not still fully understood. The development of CIMP is followed by global gene expression alterations and metabolic changes. In particular, CIMP-low colon adenocarcinoma (COAD), predominantly corresponded to consensus molecular subtype 3 (CMS3, "Metabolic") subgroup according to COAD molecular classification, is associated with elevated expression of genes participating in metabolic pathways.

METHODS

We performed bioinformatics analysis of RNA-Seq data from The Cancer Genome Atlas (TCGA) project for CIMP-high and non-CIMP COAD samples with DESeq2, clusterProfiler, and topGO R packages. Obtained results were validated on a set of fourteen COAD samples with matched morphologically normal tissues using quantitative PCR (qPCR).

RESULTS

Upregulation of multiple genes involved in glycolysis and related processes (ENO2, PFKP, HK3, PKM, ENO1, HK2, PGAM1, GAPDH, ALDOA, GPI, TPI1, and HK1) was revealed in CIMP-high tumors compared to non-CIMP ones. Most remarkably, the expression of the PKLR gene, encoding for pyruvate kinase participating in gluconeogenesis, was decreased approximately 20-fold. Up to 8-fold decrease in the expression of OGDHL gene involved in tricarboxylic acid (TCA) cycle was observed in CIMP-high tumors. Using qPCR, we confirmed the increase (4-fold) in the ENO2 expression and decrease (2-fold) in the OGDHL mRNA level on a set of COAD samples.

CONCLUSIONS

We demonstrated the association between CIMP-high status and the energy metabolism changes at the transcriptomic level in colorectal adenocarcinoma against the background of immune pathway activation. Differential methylation of at least nine CpG sites in OGDHL promoter region as well as decreased OGDHL mRNA level can potentially serve as an additional biomarker of the CIMP-high status in COAD.

Deletion of the murine ortholog of the 8q24 gene desert has anti-cancer effects in transgenic mammary cancer models

Background

The gene desert on human chromosomal band 8q24 harbors multiple genetic variants associated with common cancers, including breast cancer. The locus, including the gene desert and its flanking genes, MYC, PVT1 and FAM84B, is also frequently amplified in human breast cancer. We generated a megadeletion (MD) mouse model lacking 430-Kb of sequence orthologous to the breast cancer-associated region in the gene desert. The goals were to examine the effect of the deletion on mammary cancer development and on transcript level regulation of the candidate genes within the locus.

Methods

The MD allele was engineered using the MICER system in embryonic stem cells and bred onto 3 well-characterized transgenic models for breast cancer, namely MMTV-PyVT, MMTV-neu and C3(1)-TAg. Mammary tumor growth, latency, multiplicity and metastasis were compared between homozygous MD and wild type mice carrying the transgenes. A reciprocal mammary gland transplantation assay was conducted to distinguish mammary cell-autonomous from non-mammary cell-autonomous anti-cancer effects. Gene expression analysis was done using quantitative real-time PCR. Chromatin interactions were evaluated by 3C. Gene-specific patient outcome data were analysed using the METABRIC and TCGA data sets through the cBioPortal website.

Results

Mice homozygous for the MD allele are viable, fertile, lactate sufficiently to nourish their pups, but maintain a 10% lower body weight mainly due to decreased adiposity. The deletion interferes with mammary tumorigenesis in mouse models for luminal and basal breast cancer. In the MMTV-PyVT model the mammary cancer-reducing effects of the allele are mammary cell-autonomous. We found organ-specific effects on transcript level regulation, with Myc and Fam84b being downregulated in mammary gland, prostate and mammary tumor samples. Through analysis using the METABRIC and TCGA datasets, we provide evidence that MYC and FAM84B are frequently co-amplified in breast cancer, but in contrast with MYC, FAM84B is frequently overexpressed in the luminal subtype, whereas MYC activity affect basal breast cancer outcomes.

Conclusion

Deletion of a breast cancer-associated non-protein coding region affects mammary cancer development in 3 transgenic mouse models. We propose Myc as a candidate susceptibility gene, regulated by the gene desert locus, and a potential role for Fam84b in modifying breast cancer development.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5109-8) contains supplementary material, which is available to authorized users.

Significant association of TOX3/LOC643714 locus-rs3803662 and breast cancer risk in a cohort of Iranian population

Genome-wide association studies normally focus on low penetrance and moderate to high-frequency single nucleotide polymorphisms (SNPs), which lead to genetic susceptibility to breast cancer. In this regard, the T allele of rs3803662 has been associated with breast cancer risk and with lower expression level of TOX3. We aimed to assess the risk of breast cancer associated with this polymorphism in an Iranian population. Using Tetra Primer ARMS PCR, rs3803662 was analyzed in a total of 943 individuals (430 cases and 513 healthy controls form North East of Iran). Allele frequencies and genotype distribution were analyzed in case and control samples to find out any association using the Chi-squared test and Logistic regression. All cases were pathologically confirmed; all controls were mainly healthy individuals. Genotype frequencies were found to be in agreement with HWE in controls and cases. TOX3-rs3803662 SNP was associated with breast cancer risk in our study (T vs. C allele contrast model: OR 1.36, 95% CI 1.12-1.64, P_value = 0.002; TT vs. CT + TT dominant model: OR 0.67, 95% CI 0.51-0.87, P_value = 0.003; TT vs. CT + CC recessive model: OR 1.54, 95% CI 1.02-2.30, P_vlue = 0.036). Moreover, after adjusting for age, BMI, history of previous cancer and also family history of cancer, all results, except for the recessive model, were remained significant. TOX3-rs3803662, may confer some degrees of risk of breast cancer in Iranian population. This finding is in line with similar results in other populations. It highlights the importance of TOX3 pathway in tumorigenesis.

Inborn-like errors of metabolism are determinants of breast cancer risk, clinical response and survival: a study of human biochemical individuality

Breast cancer remains a leading cause of morbidity and mortality worldwide yet methods for early detection remain elusive. We describe the discovery and validation of biochemical signatures measured by mass spectrometry, performed upon blood samples from patients and controls that accurately identify (>95%) the presence of clinical breast cancer. Targeted quantitative MS/MS conducted upon 1225 individuals, including patients with breast and other cancers, normal controls as well as individuals with a variety of metabolic disorders provide a biochemical phenotype that accurately identifies the presence of breast cancer and predicts response and survival following the administration of neoadjuvant chemotherapy. The metabolic changes identified are consistent with inborn-like errors of metabolism and define a continuum from normal controls to elevated risk to invasive breast cancer. Similar results were observed in other adenocarcinomas but were not found in squamous cell cancers or hematologic neoplasms. The findings describe a new early detection platform for breast cancer and support a role for pre-existing, inborn-like errors of metabolism in the process of breast carcinogenesis that may also extend to other glandular malignancies.

Statement of Significance: Findings provide a powerful tool for early detection and the assessment of prognosis in breast cancer and define a novel concept of breast carcinogenesis that characterizes malignant transformation as the clinical manifestation of underlying metabolic insufficiencies.

A meta-analysis approach with filtering for identifying gene-level gene-environment interactions

There is a growing recognition that gene-environment interaction (G × E) plays a pivotal role in the development and progression of complex diseases. Despite a wealth of genetic data on various complex diseases/traits generated from association and sequencing studies, detecting G × E via genome-wide analysis remains challenging due to power issues. In genome-wide G × E studies, a common strategy to improve power is to first conduct a filtering test and retain only the genetic variants that pass the filtering step for subsequent G × E analyses. Two-stage, multistage, and unified tests have been proposed to jointly consider the filtering statistics in G × E tests. However, such G × E tests based on data from a single study may still be underpowered. Meanwhile, large-scale consortia have been formed to borrow strength across studies and populations. In this work, motivated by existing single-study G × E tests with filtering and the needs for meta-analysis G × E approaches based on consortia data, we propose a meta-analysis framework for detecting gene-based G × E effects, and introduce meta-analysis-based filtering statistics in the gene-level G × E tests. Simulations demonstrate the advantages of the proposed method-the ofGEM test. We apply the proposed tests to existing data from two breast cancer consortia to identify the genes harboring genetic variants with age-dependent penetrance (i.e., gene-age interaction effects). We develop an R software package ofGEM for the proposed meta-analysis tests.

Germline Variation and Breast Cancer Incidence: A Gene-Based Association Study and Whole-Genome Prediction of Early-Onset Breast Cancer

Background: Although germline genetics influences breast cancer incidence, published research only explains approximately half of the expected association. Moreover, the accuracy of prediction models remains low. For women who develop breast cancer early, the genetic architecture is less established.Methods: To identify loci associated with early-onset breast cancer, gene-based tests were carried out using exome array data from 3,479 women with breast cancer diagnosed before age 50 and 973 age-matched controls. Replication was undertaken in a population that developed breast cancer at all ages of onset.Results: Three gene regions were associated with breast cancer incidence: FGFR2 (P = 1.23 × 10^-5; replication P < 1.00 × 10^-6), NEK10 (P = 3.57 × 10^-4; replication P < 1.00 × 10^-6), and SIVA1 (P = 5.49 × 10^-4; replication P < 1.00 × 10^-6). Of the 151 gene regions reported in previous literature, 19 (12.5%) showed evidence of association (P < 0.05) with the risk of early-onset breast cancer in the early-onset population. To predict incidence, whole-genome prediction was implemented on a subset of 3,076 participants who were additionally genotyped on a genome wide array. The whole-genome prediction outperformed a polygenic risk score [AUC, 0.636; 95% confidence interval (CI), 0.614-0.659 compared with 0.601; 95% CI, 0.578-0.623], and when combined with known epidemiologic risk factors, the AUC rose to 0.662 (95% CI, 0.640-0.684).Conclusions: This research supports a role for variation within FGFR2 and NEK10 in breast cancer incidence, and suggests SIVA1 as a novel risk locus.Impact: This analysis supports a shared genetic etiology between women with early- and late-onset breast cancer, and suggests whole-genome data can improve risk assessment. Cancer Epidemiol Biomarkers Prev; 27(9); 1057-64. ©2018 AACR.

Genetic susceptibility markers for a breast-colorectal cancer phenotype: Exploratory results from genome-wide association studies

BACKGROUND

Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype.

METHODS

To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at P<5.0E-04 (n = 549, at 60 loci) were analyzed for replication (n = 293 cases and 2,103 controls).

RESULTS

Multiple correlated SNPs in intron 1 of the ROBO1 gene were suggestively associated with the breast-colorectal cancer phenotype in the discovery and replication data (most significant; rs7430339, Pdiscovery = 1.2E-04; rs7429100, Preplication = 2.8E-03). In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06).

CONCLUSION

The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of ROBO1, a potential tumor suppressor gene, merits further investigation.

Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157–3.100), 2.013 (95% CI = 1.227–3.302) and 1.751 (95% CI = 1.073–2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

Rat models of 17β-estradiol-induced mammary cancer reveal novel insights into breast cancer etiology and prevention

Numerous laboratory and epidemiologic studies strongly implicate endogenous and exogenous estrogens in the etiology of breast cancer. Data summarized herein suggest that the ACI rat model of 17β-estradiol (E2)-induced mammary cancer is unique among rodent models in the extent to which it faithfully reflects the etiology and biology of luminal types of breast cancer, which together constitute ~70% of all breast cancers. E2 drives cancer development in this model through mechanisms that are largely dependent upon estrogen receptors and require progesterone and its receptors. Moreover, mammary cancer development appears to be associated with generation of oxidative stress and can be modified by multiple dietary factors, several of which may attenuate the actions of reactive oxygen species. Studies of susceptible ACI rats and resistant COP or BN rats provide novel insights into the genetic bases of susceptibility and the biological processes regulated by genetic determinants of susceptibility. This review summarizes research progress resulting from use of these physiologically relevant rat models to advance understanding of breast cancer etiology and prevention.

Nutrient Sensing, Signaling and Ageing: The Role of IGF-1 and mTOR in Ageing and Age-Related Disease

Nutrient signaling through insulin/IGF-1 was the first pathway demonstrated to regulate ageing and age-related disease in model organisms. Pharmacological or dietary interventions targeting nutrient signaling pathways have been shown to robustly attenuate ageing in many organisms. Caloric restriction, the most widely studied longevity promoting intervention, works through multiple nutrient signaling pathways, while inhibition of mTOR through treatment with rapamycin reproducibly delays ageing and disease through specific inhibition of the mTOR complexes. Although the benefits of reduced insulin/IGF-1 in lifespan and health are well documented in model organisms, defining the precise role of the IGF-1 in human ageing and age-related disease has proven more difficult. Association studies provide some insight but also reveal paradoxes. Low serum IGF-1 predicts longevity, but IGF-1 decreases with age and IGF-1 therapy benefits some of age-related pathologies. Circulating IGF-1 has been associated both positively and negatively with risk of age-related diseases in humans, and in some cases both activation and inhibition of IGF-1 signaling have provided benefit in animal models of the same diseases. Interventions designed modulate the nutrient sensing signaling pathways positively or negatively are already available for clinical use, highlighting the need for a clear understanding of the role of nutrient signaling in ageing and age-related disease. This chapter examines data from model organisms and human genetic association studies, with a special emphasis on IGF-1 and mTOR, and discusses potential models for resolving the paradoxes surrounding IGF-1 data.

A functional polymorphism in TFF1 promoter is associated with the risk and prognosis of gastric cancer

Trefoil Factor 1 (TFF1, also named pS2), which serves as the gastrointestinal mucosal protector, is known as gastric-specific tumor suppressor gene. However, the genetic variants of TFF1 are still not well studied. In our study, we aim to explore the effects of tagging single nucleotide polymorphisms (tagSNPs) of TFF1 on risk and prognosis of gastric cancer. Seven tagSNPs of TFF1 gene were first analyzed in the discovery set, which was consisted of 753 cases and 950 cancer-free controls. Then, the validation set (940 cases and 1,042 controls) was used for further evaluation. Moreover, we also tested the relation between these tagSNPs and prognosis of gastric cancer (GC). A series of experiments were performed to investigate the underlying mechanisms. We found that rs3761376 AA in the promoter region of TFF1, could reduce the expression of TFF1 by affecting the binding affinity of estrogen receptor 1 (ESR1, ERα), and thereby increased the risk of GC (1.29, 1.08-1.53). Moreover, the rs3761376 AA genotype was also found associated with worse prognosis among patients receiving 5-FU based chemotherapy after surgery (1.71, 1.18-2.48). Further functional assays demonstrated that TFF1 could increase the chemosensitivity of 5-FU by modulating NF-κB targeted genes. These results identified the effect of rs3761376 on TFF1 expression, which accounted for the correlation with susceptibility and prognosis of GC; and this genetic variant may be a potential biomarker to predict the risk and survival of GC.

Profile of common prostate cancer risk variants in an unscreened Romanian population

To find sequence variants affecting prostate cancer (PCA) susceptibility in an unscreened Romanian population we use a genome‐wide association study (GWAS). The study population included 990 unrelated pathologically confirmed PCA cases and 1034 male controls. DNA was genotyped using Illumina SNP arrays, and 24.295.558 variants were imputed using the 1000 Genomes data set. An association test was performed between the imputed markers and PCA. A systematic literature review for variants associated with PCA risk identified 115 unique variants that were tested in the Romanian sample set. Thirty of the previously reported SNPs replicated (P‐value < 0.05), with the strongest associations observed at: 8q24.21, 11q13.3, 6q25.3, 5p15.33, 22q13.2, 17q12 and 3q13.2. The replicated variants showing the most significant association in Romania are rs1016343 at 8q24.21 (P = 2.2 × 10⁻⁴), rs7929962 at 11q13.3 (P = 2.7 × 10⁻⁴) and rs9364554 at 6q25.2 (P = 4.7 × 10⁻⁴). None of the variants tested in the Romanian GWAS reached genome‐wide significance (P‐value <5 × 10⁻⁸) but 807 markers had P‐values <1 × 10⁻⁴. Here, we report the results of the first GWAS of PCA performed in a Romanian population. Our study provides evidence that a substantial fraction of previously validated PCA variants associate with risk in this unscreened Romanian population.

The PRMT5/WDR77 complex regulates alternative splicing through ZNF326 in breast cancer

We observed overexpression and increased intra-nuclear accumulation of the PRMT5/WDR77 in breast cancer cell lines relative to immortalized breast epithelial cells. Utilizing mass spectrometry and biochemistry approaches we identified the Zn-finger protein ZNF326, as a novel interaction partner and substrate of the nuclear PRMT5/WDR77 complex. ZNF326 is symmetrically dimethylated at arginine 175 (R175) and this modification is lost in a PRMT5 and WDR77-dependent manner. Loss of PRMT5 or WDR77 in MDA-MB-231 cells leads to defects in alternative splicing, including inclusion of A-T rich exons in target genes, a phenomenon that has previously been observed upon loss of ZNF326. We observed that the alternatively spliced transcripts of a subset of these genes, involved in proliferation and tumor cell migration like REPIN1/AP4, ST3GAL6, TRNAU1AP and PFKM are degraded upon loss of PRMT5. In summary, we have identified a novel mechanism through which the PRMT5/WDR77 complex maintains the balance between splicing and mRNA stability through methylation of ZNF326.

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Breast cancer genetics in young women: What do we know?

Breast cancer (BC) in young women, generally defined in oncology as women who are 40 years of age or younger, represents 2 out of 10 BC cases in developing countries. Several research studies, including genetic cancer panel tests, genome-wide association studies, expression analyses and polymorphisms reports, have found that young women with BC exhibit a higher genetic susceptibility and specific genomic signature compared to postmenopausal women with BC. Thus, international guidelines recommend genetic counseling for this age population. This review presents the current state of the art of genetics and genomics with regards to young women with BC.

Limited influence of germline genetic variation on all-cause mortality in women with early onset breast cancer: evidence from gene-based tests, single-marker regression, and whole-genome prediction

PURPOSE

Women diagnosed with breast cancer have heterogeneous survival outcomes that cannot be fully explained by known prognostic factors, and germline variation is a plausible but unconfirmed risk factor.

METHODS

We used three approaches to test the hypothesis that germline variation drives some differences in survival: mortality loci identification, tumor aggressiveness loci identification, and whole-genome prediction. The 2954 study participants were women diagnosed with breast cancer before age 50, with a median follow-up of 15 years who were genotyped on an exome array. We first searched for loci in gene regions that were associated with all-cause mortality. We next searched for loci in gene regions associated with five histopathological characteristics related to tumor aggressiveness. Last, we also predicted 10-year all-cause mortality on a subset of 1903 participants (3,245,343 variants after imputation) using whole-genome prediction methods.

RESULTS

No risk loci for mortality or tumor aggressiveness were identified. This null result persisted when restricting to women with estrogen receptor-positive tumors, when examining suggestive loci in an independent study, and when restricting to previously published risk loci. Additionally, the whole-genome prediction model also found no evidence to support an association.

CONCLUSION

Despite multiple complementary approaches, our study found no evidence that mortality in women with early onset breast cancer is influenced by germline variation.

DNA Methylation Targets Influenced by Bisphenol A and/or Genistein Are Associated with Survival Outcomes in Breast Cancer Patients

Early postnatal exposures to Bisphenol A (BPA) and genistein (GEN) have been reported to predispose for and against mammary cancer, respectively, in adult rats. Since the changes in cancer susceptibility occurs in the absence of the original chemical exposure, we have investigated the potential of epigenetics to account for these changes. DNA methylation studies reveal that prepubertal BPA exposure alters signaling pathways that contribute to carcinogenesis. Prepubertal exposure to GEN and BPA + GEN revealed pathways involved in maintenance of cellular function, indicating that the presence of GEN either reduces or counters some of the alterations caused by the carcinogenic properties of BPA. We subsequently evaluated the potential of epigenetic changes in the rat mammary tissues to predict survival in breast cancer patients via the Cancer Genomic Atlas (TCGA). We identified 12 genes that showed strong predictive values for long-term survival in estrogen receptor positive patients. Importantly, two genes associated with improved long term survival, HPSE and RPS9, were identified to be hypomethylated in mammary glands of rats exposed prepuberally to GEN or to GEN + BPA respectively, reinforcing the suggested cancer suppressive properties of GEN.