Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer

Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

FGFR2-triggered autophagy and activation of Nrf-2 reduce breast cancer cell response to anti-ER drugs

BACKGROUND

Genetic abnormalities in the FGFR signalling occur in 40% of breast cancer (BCa) patients resistant to anti-ER therapy, which emphasizes the potential of FGFR-targeting strategies. Recent findings indicate that not only mutated FGFR is a driver of tumour progression but co-mutational landscapes and other markers should be also investigated. Autophagy has been recognized as one of the major mechanisms underlying the role of tumour microenvironment in promotion of cancer cell survival, and resistance to anti-ER drugs. The selective autophagy receptor p62/SQSTM1 promotes Nrf-2 activation by Keap1/Nrf-2 complex dissociation. Herein, we have analysed whether the negative effect of FGFR2 on BCa cell response to anti-ER treatment involves the autophagy process and/or p62/Keap1/Nrf-2 axis.

METHODS

The activity of autophagy in ER-positive MCF7 and T47D BCa cell lines was determined by analysis of expression level of autophagy markers (p62 and LC3B) and monitoring of autophagosomes' maturation. Western blot, qPCR and proximity ligation assay were used to determine the Keap1/Nrf-2 interaction and Nrf-2 activation. Analysis of 3D cell growth in Matrigel® was used to assess BCa cell response to applied treatments. In silico gene expression analysis was performed to determine FGFR2/Nrf-2 prognostic value.

RESULTS

We have found that FGFR2 signalling induced autophagy in AMPKα/ULK1-dependent manner. FGFR2 activity promoted dissociation of Keap1/Nrf-2 complex and activation of Nrf-2. Both, FGFR2-dependent autophagy and activation of Nrf-2 were found to counteract the effect of anti-ER drugs on BCa cell growth. Moreover, in silico analysis showed that high expression of NFE2L2 (gene encoding Nrf-2) combined with high FGFR2 expression was associated with poor relapse-free survival (RFS) of ER+ BCa patients.

CONCLUSIONS

This study revealed the unknown role of FGFR2 signalling in activation of autophagy and regulation of the p62/Keap1/Nrf-2 interdependence, which has a negative impact on the response of ER+ BCa cells to anti-ER therapies. The data from in silico analyses suggest that expression of Nrf-2 could act as a marker indicating potential benefits of implementation of anti-FGFR therapy in patients with ER+ BCa, in particular, when used in combination with anti-ER drugs.

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

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

The sequence kernel association test for multicategorical outcomes

Disease heterogeneity is ubiquitous in biomedical and clinical studies. In genetic studies, researchers are increasingly interested in understanding the distinct genetic underpinning of subtypes of diseases. However, existing set-based analysis methods for genome-wide association studies are either inadequate or inefficient to handle such multicategorical outcomes. In this paper, we proposed a novel set-based association analysis method, sequence kernel association test (SKAT)-MC, the sequence kernel association test for multicategorical outcomes (nominal or ordinal), which jointly evaluates the relationship between a set of variants (common and rare) and disease subtypes. Through comprehensive simulation studies, we showed that SKAT-MC effectively preserves the nominal type I error rate while substantially increases the statistical power compared to existing methods under various scenarios. We applied SKAT-MC to the Polish breast cancer study (PBCS), and identified gene FGFR2 was significantly associated with estrogen receptor (ER)+ and ER- breast cancer subtypes. We also investigated educational attainment using UK Biobank data (N = 127 , 127 $N=127,127$ ) with SKAT-MC, and identified 21 significant genes in the genome. Consequently, SKAT-MC is a powerful and efficient analysis tool for genetic association studies with multicategorical outcomes. A freely distributed R package SKAT-MC can be accessed at https://github.com/Zhiwen-Owen-Jiang/SKATMC.

FGFR2 Controls Growth, Adhesion and Migration of Nontumorigenic Human Mammary Epithelial Cells by Regulation of Integrin β1 Degradation

The role of fibroblast growth factor receptor 2 (FGFR2), an important mediator of stromal paracrine and autocrine signals, in mammary gland morphogenesis and breast cancer has been extensively studied over the last years. However, the function of FGFR2 signalling in the initiation of mammary epithelial oncogenic transformation remains elusive. Here, FGFR2-dependent behaviour of nontumorigenic model of mammary epithelial cells was studied. In vitro analyses demonstrated that FGFR2 regulates epithelial cell communication with extracellular matrix (ECM) proteins. Silencing of FGFR2 significantly changed the phenotype of cell colonies in three-dimensional cultures, decreased integrins α2, α5 and β1 protein levels and affected integrin-driven processes, such as cell adhesion and migration. More detailed analysis revealed the FGFR2 knock-down-induced proteasomal degradation of integrin β1. Analysis of RNA-seq databases showed significantly decreased FGFR2 and ITGB1 mRNA levels in breast tumour samples, when compared to non-transformed tissues. Additionally, high risk healthy individuals were found to have disrupted correlation profiles of genes associated with FGFR2 and integrin signalling, cell adhesion/migration and ECM remodelling. Taken together, our results strongly suggest that FGFR2 loss with concomitant integrin β1 degradation is responsible for deregulation of epithelial cell-ECM interactions and this process may play an important role in the initiation of mammary gland epithelial tumorigenesis.

Association of the Estrogen Receptor 1 Polymorphisms rs2046210 and rs9383590 with the Risk, Age at Onset and Prognosis of Breast Cancer

Estrogen receptor α (ERα), encoded by the ESR1 gene, is a key prognostic and predictive biomarker firmly established in routine diagnostics and as a therapeutic target of breast cancer, and it has a central function in breast cancer biology. Genetic variants at 6q25.1, containing the ESR1 gene, were found to be associated with breast cancer susceptibility. The rs2046210 and rs9383590 single nucleotide variants (SNVs) are located in the same putative enhancer region upstream of ESR1 and were separately identified as candidate causal variants responsible for these associations. Here, both SNVs were genotyped in a hospital-based case-control study of 409 female breast cancer patients and 422 female controls of a Central European (Austrian) study population. We analyzed the association of both SNVs with the risk, age at onset, clinically and molecularly relevant characteristics and prognosis of breast cancer. We also assessed the concordances between both SNVs and the associations of each SNV conditional on the other SNV. The minor alleles of both SNVs were found to be non-significantly associated with an increased breast cancer risk. Significant associations were found in specific subpopulations, particularly in patients with an age younger than 55 years. The minor homozygotes of rs2046210 and the minor homozygotes plus heterozygotes of rs9383590 exhibited a several-years-younger age at onset than the common homozygotes, which was more pronounced in ER-positive and luminal patients. Importantly, the observed associations of each SNV were not consistently nullified upon correction for the other SNV nor upon analyses in common homozygotes for the other SNV. We conclude that both SNVs remain independent candidate causal variants.

To Investigate Growth Factor Receptor Targets and Generate Cancer Targeting Inhibitors

Receptor tyrosine kinase (RTK) regulates multiple pathways, including Mitogenactivated protein kinases (MAPKs), PI3/AKT, JAK/STAT pathway, etc. which has a significant role in the progression and metastasis of tumor. As RTK activation regulates numerous essential bodily processes, including cell proliferation and division, RTK dysregulation has been identified in many types of cancers. Targeting RTK is a significant challenge in cancer due to the abnormal upregulation and downregulation of RTK receptors subfamily EGFR, FGFR, PDGFR, VEGFR, and HGFR in the progression of cancer, which is governed by multiple RTK receptor signalling pathways and impacts treatment response and disease progression. In this review, an extensive focus has been carried out on the normal and abnormal signalling pathways of EGFR, FGFR, PDGFR, VEGFR, and HGFR and their association with cancer initiation and progression. These are explored as potential therapeutic cancer targets and therefore, the inhibitors were evaluated alone and merged with additional therapies in clinical trials aimed at combating global cancer.

The correlation of leukocyte-specific protein 1 (LSP1) rs3817198(T>C) polymorphism with breast cancer: A meta-analysis

BACKGROUND

Multiple studies have investigated the correlation of single nucleotide polymorphisms (SNPs) in leukocyte-specific protein 1 (LSP1) with susceptibility to breast cancer (BC) and have yielded inconsistent conclusions, particularly rs3817198(T > C). Consequently, we performed a meta-analysis to estimate this relationship more comprehensively.

METHODS

Four databases were utilized to locate eligible publications: PubMed, Embase, Web of Science, and China National Knowledge Infrastructure. This meta-analysis included 14 studies, including 22 reports of 33194 cases and 36661 controls. The relationship of rs3817198 polymorphism with breast cancer was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). The LSP1 co-expression network was constructed by STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using DAVIDE. Download TCGA breast cancer mRNA-seq data and analyze the relationship between LSP1 expression and breast cancer chemotherapy sensitivity.

RESULTS

The results indicated that rs3817198(T > C) was positively correlated to with breast malignancy (dominant model: OR = 1.11, 95%CI = 1.06-1.17; recessive model: OR = 1.10, 95%CI = 1.04-1.15; heterozygous model: OR = 1.09, 95%CI = 1.04-1.15; homozygous model: OR = 1.18, 95%CI = 1.09-1.28; additive model: OR = 1.09, 95%CI = 1.05-1.13), among Caucasians and Asians. However, rs3817198(T > C) may reduce the risk of breast carcinoma in Africans. Rs3817198(T > C) might result in breast carcinoma in individuals with BRCA1 and BRCA2 variants and can contribute to estrogen receptor (ER)-positive breast carcinoma. The expression of LSP1 was inversely correlated with the IC50 of doxorubicin (P = 8.91e-15, Cor = -0.23), 5-fluorouracil (P = 1.18e-22, Cor = -0.29), and cisplatin (P = 1.35e-42, Cor = -0.40).

CONCLUSION

Our study identified that LSP1 rs3817198 polymorphism might result in breast malignancy, particularly among Caucasians and Asians, but lower breast cancer susceptibility in African populations. The expression of LSP1 was negatively correlated with the IC50 of doxorubicin, 5-fluorouracil, and cisplatin.

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

BACKGROUND

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

METHODS

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

RESULT

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

CONCLUSION

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

Inference for High-Dimensional Censored Quantile Regression

With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes. To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression. This paper proposes a novel procedure to draw inference on all predictors within the framework of global censored quantile regression, which investigates covariate-response associations over an interval of quantile levels, instead of a few discrete values. The proposed estimator combines a sequence of low dimensional model estimates that are based on multi-sample splittings and variable selection. We show that, under some regularity conditions, the estimator is consistent and asymptotically follows a Gaussian process indexed by the quantile level. Simulation studies indicate that our procedure can properly quantify the uncertainty of the estimates in high dimensional settings. We apply our method to analyze the heterogeneous effects of SNPs residing in lung cancer pathways on patients' survival, using the Boston Lung Cancer Survivor Cohort, a cancer epidemiology study on the molecular mechanism of lung cancer.

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

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.

Association Between Single-Nucleotide Polymorphisms in Breast Cancer Susceptibility Genes and Clinicopathological Characteristics

Objective

The purpose of the present study was to evaluate the associations between seven tagging single nucleotide polymorphisms (tSNPs) and risk of breast cancer assessed by tumor pathological characteristics and body mass index (BMI).

Methods

Seven tSNPs of four breast cancer susceptibility genes were analyzed in 734 Chinese women with breast cancer and 672 age-matched healthy controls; then, the association with clinicopathological characteristics, BMI, molecular subtype, TNM (T, tumor; N, lymph node; M, metastasis) staging and lymph node status was determined by unconditional logistic regression.

Results

Rs12951053 in TP53 and rs16945628 in BRIP1, displayed increased risk of breast cancer in the BMI ≧ 25 kg/m² group (OR=1.50, 95% CI: 1.02–2.21, P=0.041 and OR=1.92, 95% CI: 1.13–3.26, P=0.015, respectively). The other five tSNPs (rs1805812, rs2735385 and rs6999227 in NBS1, rs7220719 in BRIP1 and rs2299941 in PTEN) displayed a decreased risk of breast cancer in the 18.5≤BMI<25 kg/m² group. Rs12951053 in TP53 and rs7220719 in BRIP1 exhibited an increased risk of triple‐negative breast cancer (OR=1.50, 95% CI: 1.05–2.15, P=0.026 and OR=2.13, 95% CI: 1.05–4.29, P=0.032, respectively), but three tSNPs in NBS1 (rs1805812, rs2735385 and rs6999227) all displayed a negative association with both luminal B and triple-negative breast cancer. The tSNP rs2299941 in PTEN also exhibited a negative association with each molecular subtype, except triple-negative breast cancer. The majority of tSNPs displayed a negative association with stage II or III breast cancer. Most tSNPs showed a negative association with breast cancer that was lymph node negative or with 1–3 positive nodes. Only rs12951053 in TP53 displayed a positive association with lymph node-negative breast cancer (OR=1.43, 95% CI: 1.08–1.91, P=0.013).

Conclusion

The majority of tSNPs displayed a negative association with breast cancer and only a few tSNPs (rs12951053 in TP53, rs16945628 and rs7220719 in BRIP1) showed an increased risk of breast cancer as defined by clinicopathological characteristics.

Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules

The use of biological networks such as protein-protein interaction and transcriptional regulatory networks is becoming an integral part of genomics research. However, these networks are not static, and during phenotypic transitions like disease onset, they can acquire new "communities" (or highly interacting groups) of genes that carry out cellular processes. Disease communities can be detected by maximizing a modularity-based score, but since biological systems and network inference algorithms are inherently noisy, it remains a challenge to determine whether these changes represent real cellular responses or whether they appeared by random chance. Here, we introduce Constrained Random Alteration of Network Edges (CRANE), a method for randomizing networks with fixed node strengths. CRANE can be used to generate a null distribution of gene regulatory networks that can in turn be used to rank the most significant changes in candidate disease communities. Compared to other approaches, such as consensus clustering or commonly used generative models, CRANE emulates biologically realistic networks and recovers simulated disease modules with higher accuracy. When applied to breast and ovarian cancer networks, CRANE improves the identification of cancer-relevant GO terms while reducing the signal from non-specific housekeeping processes.

Identification and characterization of functional long noncoding RNAs in cancer

Long noncoding RNAs (lncRNAs) have emerged as key regulators in a variety of cellular processes that influence disease states. In particular, many lncRNAs are genetically or epigenetically deregulated in cancer. However, whether lncRNA alterations are passengers acquired during cancer progression or can act as tumorigenic drivers is a topic of ongoing investigation. In this review, we examine the current methodologies underlying the identification of cancer-associated lncRNAs and highlight important considerations for evaluating their biological significance as cancer drivers.

Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort

PURPOSE

We evaluated the performance of the recently extended Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA version 5) in a Dutch prospective cohort, using a polygenic risk score (PRS) based on 313 breast cancer (BC)-associated variants (PRS313) and other, nongenetic risk factors.

METHODS

Since 1989, 6522 women without BC aged 45 or older of European descent have been included in the Rotterdam Study. The PRS313 was calculated per 1 SD in controls from the Breast Cancer Association Consortium (BCAC). Cox regression analysis was performed to estimate the association between the PRS313 and incident BC risk. Cumulative 10-year risks were calculated with BOADICEA including different sets of variables (age, risk factors and PRS313). C-statistics were used to evaluate discriminative ability.

RESULTS

In total, 320 women developed BC. The PRS313 was significantly associated with BC (hazard ratio [HR] per SD of 1.56, 95% confidence interval [CI] [1.40-1.73]). Using 10-year risk estimates including age and the PRS313, other risk factors improved the discriminatory ability of the BOADICEA model marginally, from a C-statistic of 0.636 to 0.653.

CONCLUSIONS

The effect size of the PRS313 is highly reproducible in the Dutch population. Our results validate the BOADICEA v5 model for BC risk assessment in the Dutch general population.

Cumulative evidence of relationships between multiple variants in 8q24 region and cancer incidence

Genome-wide association studies (GWAS) have identified multiple independent cancer susceptibility loci at chromosome 8q24. We aimed to evaluate the associations between variants in the 8q24 region and cancer susceptibility. A comprehensive research synopsis and meta-analysis was performed to evaluate associations between 28 variants in 8q24 and risk of 7 cancers using data from 103 eligible articles totaling 146,932 cancer cases and 219,724 controls. Results: 20 variants were significantly associated with risk of prostate cancer, colorectal cancer, thyroid cancer, breast cancer, bladder cancer, stomach cancer, and glioma, including 1 variant associated with prostate cancer, colorectal cancer, and thyroid cancer. Cumulative epidemiological evidence of an association was graded as strong for DG8S737 -8 allele, rs10090154, rs7000448 in prostate cancer, rs10808556 in colorectal cancer, rs55705857 in gliomas, rs9642880 in bladder cancer, moderate for rs16901979, rs1447295, rs6983267, rs7017300, rs7837688, rs1016343, rs620861, rs10086908 associated in prostate cancer, rs10505477, rs6983267 in colorectal cancer, rs6983267 in thyroid cancer, rs13281615 in breast cancer, and rs1447295 in stomach cancer, weak for rs6983561, rs13254738, rs7008482, rs4242384 in prostate cancer. Data from ENCODE suggested that these variants with strong evidence and other correlated variants might fall within putative functional regions. Our study provides summary evidence that common variants in the 8q24 are associated with risk of multiple cancers in this large-scale research synopsis and meta-analysis. Further studies are needed to explore the mechanisms underlying variants in the 8q24 involved in various human cancers.

Variants in the 8q24 region associated with risk of breast cancer: Systematic research synopsis and meta-analysis

Breast cancer is a molecularly heterogeneous disorder associated with high lethal malignant tumors among women worldwide. Genetic factors play an important role in breast cancer development. Several single nucleotide polymorphisms in the 8q24 region associated with risk of breast cancer have been identified. Fifteen studies including 32,955 cases and 43,716 controls were collected to conduct a meta-analysis to evaluate the associations between variants in 8q24 region and risk of breast cancer. Our study showed that only rs13281615 is associated with breast cancer risk in this large-scale research synopsis and meta-analysis. Further studies are needed to explore the role of the 8q24 variants in the development of breast cancer.

Long non-coding RNA, LINC01614 as a potential biomarker for prognostic prediction in breast cancer

Background

Dysregulated long non-coding RNAs (lncRNAs) may serve as potential biomarkers of cancers including breast cancer (BRCA). This study aimed to identify lncRNAs with strong prognostic value for BRCA.

Methods

LncRNA expression profiles of 929 tissue samples were downloaded from TANRIC database. We performed differential expression analysis between paired BRCA and adjacent normal tissues. Survival analysis was used to identify lncRNAs with prognostic value. Univariate and multivariate Cox regression analyses were performed to confirm the independent prognostic value of potential lncRNAs. Dysregulated signaling pathways associated with lncRNA expression were evaluated using gene set enrichment analysis.

Results

We found that a total of 398 lncRNAs were significantly differentially expressed between BRCA and adjacent normal tissues (adjusted P value <= 0.0001 and |logFC| >= 1). Additionally, 381 potential lncRNAs were correlated Overall Survival (OS) (P value < 0.05). A total of 48 lncRNAs remained when differentially expressed lncRNAs overlapped with lncRNAs that had prognostic value. Among the 48 lncRNAs, one lncRNA (LINC01614) had stronger prognostic value and was highly expressed in BRCA tissues. LINC01614 expression was validated as an independent prognostic factor using univariate and multivariate analyses. Higher LINC01614 expression was observed in several molecular subgroups including estrogen receptors+, progesterone receptors+ and human epidermal growth factor receptor 2 (HER2)+ subgroup, respectively. Also, BRCA carrying one of four gene mutations had higher expression of LINC01614 including AOAH, CIT, HER2 and ODZ1. Higher expression of LINC01614 was positively correlated with several gene sets including TGF-β1 response, CDH1 signals and cell adhesion pathways.

Conclusions

A novel lncRNA LINC01614 was identified as a potential biomarker for prognosis prediction of BRCA. This study emphasized the importance of LINC01614 and further research should be focused on it.

Relationships between SNPs and prognosis of breast cancer and pathogenic mechanism

Background

Association between several single‐nucleotide polymorphisms (SNPs) and breast cancer risk has been identified through genome‐wide association studies (GWAS), but little is known about their significance in patients’ prognosis. We screened SNPs which were related to the prognosis of breast cancer in Henan Han population, analyzed relevant genes by bioinformatics in database, and further constructed the genetic regulatory network involved in the pathogenesis of breast cancer.

Methods

We evaluated five SNPs in 232 cases of breast cancer at the Affiliated Tumor Hospital of Zhengzhou University. Relationships between five SNPs, clinical prognostic indicators, and disease‐free survival (DFS) were evaluated by Kaplan–Meier analysis and Cox proportional hazards model. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of genes and Genome (KEGG) analysis were carried out to preliminarily establish genetic regulation network model of breast cancer. Bayesian algorithm was used to optimize the model.

Results

The multivariate Cox proportional hazards model confirmed that SNP rs3803662 (TOX3/TNRC9) had correlation with DFS independently. In the multivariate Cox proportional hazards model, compared with GA/AA, GG increased the recurrent risk of breast cancer (p = .021, hazard ratio [HR] = 2.914). GO analysis showed that the function of TOX3/TNRC9 included biological_process, molecular_function, and cellular_component. According to KEGG signaling pathway database, the map of breast cancer‐related gene regulatory network was obtained. IGF‐IGF1R‐PI3K‐Akt‐mTOR‐S6K was the best possible pathway for the differentiation of breast cancer cells in this network and ER‐TOX3/TNRC9 was the best possible pathway for the survival of tumor cells in this network by Bayesian theorem optimization.

Conclusions

SNP rs3803662 (TOX3/TNRC9) is an independent prognostic factor for breast cancer in Henan Han Population. ER‐TOX3/TNRC9 is the best possible pathway involved in the pathogenesis of breast cancer.

A Review of the Hereditary Component of Triple Negative Breast Cancer: High- and Moderate-Penetrance Breast Cancer Genes, Low-Penetrance Loci, and the Role of Nontraditional Genetic Elements

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.

FGFs/FGFRs-dependent signalling in regulation of steroid hormone receptors - implications for therapy of luminal breast cancer

Stromal stimuli mediated by growth factor receptors, leading to ligand-independent activation of steroid hormone receptors, have long been implicated in development of breast cancer resistance to endocrine therapy. Mutations in fibroblast growth factor receptor (FGFR) genes have been associated with a higher incidence and progression of breast cancer. Increasing evidence suggests that FGFR-mediated interaction between luminal invasive ductal breast carcinoma (IDC) and its microenvironment contributes to the progression to hormone-independence. Therapeutic strategies based on FGFR inhibitors hold promise for overcoming resistance to the ER-targeting treatment. A series of excellent reviews discuss a potential role of FGFR in development of IDC. Here, we provide a concise updated summary of existing literature on FGFR-mediated signalling with an emphasis on an interaction between FGFR and estrogen/progesterone receptors (ER/PR) in IDC. Focusing on the regulatory role of tumour microenvironment in the activity of steroid hormone receptors, we compile the available functional data on FGFRs-mediated signalling, as a fundamental mechanism of luminal IDC progression and failure of anti-ER treatment. We also highlight the translational value of the presented findings and summarize ongoing oncologic clinical trials investigating FGFRs inhibition in interventional studies in breast cancer.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas

Importance

African Americans have the highest breast cancer mortality rate. Although racial difference in the distribution of intrinsic subtypes of breast cancer is known, it is unclear if there are other inherent genomic differences that contribute to the survival disparities.

Objectives

To investigate racial differences in breast cancer molecular features and survival and to estimate the heritability of breast cancer subtypes.

Design, Setting, and Participants

Among a convenience cohort of patients with invasive breast cancer, breast tumor and matched normal tissue sample data (as of September 18, 2015) were obtained from The Cancer Genome Atlas.

Main Outcomes and Measures

Breast cancer–free interval, tumor molecular features, and genetic variants.

Results

Participants were 930 patients with breast cancer, including 154 black patients of African ancestry (mean [SD] age at diagnosis, 55.66 [13.01] years; 98.1% [n = 151] female) and 776 white patients of European ancestry (mean [SD] age at diagnosis, 59.51 [13.11] years; 99.0% [n = 768] female). Compared with white patients, black patients had a worse breast cancer-free interval (hazard ratio, HR=1.67; 95% CI, 1.02-2.74; P = .043). They had a higher likelihood of basal-like (odds ratio, 3.80; 95% CI, 2.46-5.87; P < .001) and human epidermal growth factor receptor 2 (ERBB2 [formerly HER2])–enriched (odds ratio, 2.22; 95% CI, 1.10-4.47; P = .027) breast cancer subtypes, with the Luminal A subtype as the reference. Blacks had more TP53 mutations and fewer PIK3CA mutations than whites. While most molecular differences were eliminated after adjusting for intrinsic subtype, the study found 16 DNA methylation probes, 4 DNA copy number segments, 1 protein, and 142 genes that were differentially expressed, with the gene-based signature having an excellent capacity for distinguishing breast tumors from black vs white patients (cross-validation C index, 0.878). Using germline genotypes, the heritability of breast cancer subtypes (basal vs nonbasal) was estimated to be 0.436 (P = 1.5 × 10−14). The estrogen receptor–positive polygenic risk score built from 89 known susceptibility variants was higher in blacks than in whites (difference, 0.24; P = 2.3 × 10−5), while the estrogen receptor–negative polygenic risk score was much higher in blacks than in whites (difference, 0.48; P = 2.8 × 10−11).

Conclusions and Relevance

On the molecular level, after adjusting for intrinsic subtype frequency differences, this study found a modest number of genomic differences but a significant clinical survival outcome difference between blacks and whites in The Cancer Genome Atlas data set. Moreover, more than 40% of breast cancer subtype frequency differences could be explained by genetic variants. These data could form the basis for the development of molecular targeted therapies to improve clinical outcomes for the specific subtypes of breast cancers that disproportionately affect black women. Findings also indicate that personalized risk assessment and optimal treatment could reduce deaths from aggressive breast cancers for black women.

Enhancer Domains in Gastrointestinal Stromal Tumor Regulate KIT Expression and Are Targetable by BET Bromodomain Inhibition

Gastrointestinal stromal tumor (GIST) is a mesenchymal neoplasm characterized by activating mutations in the related receptor tyrosine kinases KIT and PDGFRA. GIST relies on expression of these unamplified receptor tyrosine kinase (RTK) genes through a large enhancer domain, resulting in high expression levels of the oncogene required for tumor growth. Although kinase inhibition is an effective therapy for many patients with GIST, disease progression from kinase-resistant mutations is common and no other effective classes of systemic therapy exist. In this study, we identify regulatory regions of the KIT enhancer essential for KIT gene expression and GIST cell viability. Given the dependence of GIST upon enhancer-driven expression of RTKs, we hypothesized that the enhancer domains could be therapeutically targeted by a BET bromodomain inhibitor (BBI). Treatment of GIST cells with BBIs led to cell-cycle arrest, apoptosis, and cell death, with unique sensitivity in GIST cells arising from attenuation of the KIT enhancer domain and reduced KIT gene expression. BBI treatment in KIT-dependent GIST cells produced genome-wide changes in the H3K27ac enhancer landscape and gene expression program, which was also seen with direct KIT inhibition using a tyrosine kinase inhibitor (TKI). Combination treatment with BBI and TKI led to superior cytotoxic effects in vitro and in vivo, with BBI preventing tumor growth in TKI-resistant xenografts. Resistance to select BBI in GIST was attributable to drug efflux pumps. These results define a therapeutic vulnerability and clinical strategy for targeting oncogenic kinase dependency in GIST. SIGNIFICANCE: Expression and activity of mutant KIT is essential for driving the majority of GIST neoplasms, which can be therapeutically targeted using BET bromodomain inhibitors.

Senescent Breast Luminal Cells Promote Carcinogenesis through Interleukin-8-Dependent Activation of Stromal Fibroblasts

Aging and stress promote senescence, which has intrinsic tumor suppressor functions and extrinsic tumor promoting properties. Therefore, it is of utmost importance to delineate the effects of senescence inducers on the various types of cells that compose the different organs. We show here that primary normal breast luminal (NBL) cells are more sensitive than their corresponding stromal fibroblasts to proliferative as well as oxidative damage-induced senescence. Like fibroblasts, senescent NBL cells secreted elevated amounts of various cytokines, including interleukin-6 (IL-6) and IL-8, and expressed high levels of p16, p21, and p53, while lamin B1 was downregulated. When senescent, luminal cells activated stromal fibroblasts in an IL-8-dependent manner, through the activation of the STAT3 pathway. These myofibroblasts promoted the epithelial-to-mesenchymal transition and the stemness processes in breast cancer cells in a paracrine manner both in vitro and in a breast cancer animal model. These results show the role of senescent breast luminal cells in promoting the inflammatory/carcinogenic microenvironment through the activation of fibroblasts in an IL-8-dependent manner.

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.

Impact of phosphorylated insulin-like growth factor-1 receptor on the outcome of breast cancer patients and the prognostic value of its alteration during neoadjuvant chemotherapy

The expression of insulin-like growth factor-1 receptor (IGF-1R), which is involved in the genesis and progression of breast cancer, is thought to be associated with the overall survival (OS) of patients. However, the predictive and prognostic significance of the IGF-1R expression in breast cancer remains controversial. The present study aimed to identify the factors associated with the levels of phosphorylated (p)-IGF-1R in breast cancer, their impact on the outcomes of breast cancer patients, and the prognostic value of alterations of p-IGF-1R during neoadjuvant chemotherapy (NAC). The present study included 348 female breast cancer patients whose paraffin-embedded tumor tissue sections had been collected by biopsy and/or resection, among which the pre-NAC and post-NAC sections were available from 40 patients. Human epidermal growth factor receptor 2 (HER2) positivity and molecular subtype were significantly associated with the presence of p-IGF-1R in the tumor tissue (P<0.05). Patients with p-IGF-1R present in the tumor tissue had a shorter OS (P=0.003). The p-IGF-1R levels in the tumor after NAC differed significantly from those prior to NAC (P=0.005); however, this alteration in p-IGF-1R levels was not associated with a shorter OS. In parallel with HER2, p-IGF-1R appears to be a promising indicator for predicting clinical outcomes and may be an attractive target for improving the efficacy of antitumor therapy, particularly for patients with HER2-negative, estrogen receptor-positive and luminal B tumors.

The LSP1 rs3817198 T > C polymorphism contributes to increased breast cancer risk: a meta-analysis of twelve studies

The association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk has been widely investigated, but remains controversial. We therefore undertook a comprehensive meta-analysis to provide a high-quality evaluation of this association. A literature search was performed among Pubmed, EMBASE and Chinese National Knowledge Infrastructure (CNKI) databases prior to July 31, 2016, and the strength of the association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk was assessed based on odds ratio (OR) and 95% confidence interval (95% CI). In total, 12 studies with 50,525 cases and 54,302 controls were included. Pooled risk estimates indicated a significant association between the LSP1 rs3817198 T > C polymorphism and breast cancer risk. Analysis of cases stratified based on ethnicity suggested that the association was significant in both Caucasian and Asian populations. Stratification based on source of controls revealed an association only in population-based studies. These findings indicate the LSP1 rs3817198 T > C polymorphism is associated with increased risk of breast cancer, especially in Caucasian and Asian populations. Large, well-designed studies with different ethnicities are still needed to verify our findings.

Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future

Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Association between FGFR2 (rs2981582, rs2420946 and rs2981578) polymorphism and breast cancer susceptibility: a meta-analysis

The association between fibroblast growth factor receptor 2 (FGFR2) polymorphism and breast cancer (BC) susceptibility remains inconclusive. The purpose of this systematic review was to evaluate the relationship between FGFR2 (rs2981582, rs2420946 and rs2981578) polymorphism and BC risk. PubMed, Web of science and the Cochrane Library databases were searched before October 11, 2015 to identify relevant studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the strength of associations. Sensitivity and subgroup analyses were conducted. Thirty-five studies published from 2007 to 2015 were included in this meta-analysis. The pooled results showed that there was significant association between all the 3 variants and BC risk in any genetic model. Subgroup analysis was performed on rs2981582 and rs2420946 by ethnicity and Source of controls, the effects remained in Asians, Caucasians, population-based and hospital-based groups. We did not carryout subgroup analysis on rs2981578 for the variant included only 3 articles. This meta-analysis of case-control studies provides strong evidence that FGFR2 (rs2981582, rs2420946 and rs2981578) polymorphisms were significantly associated with the BC risk. For rs2981582 and rs2420946, the association remained significant in Asians, Caucasians, general populations and hospital populations. However, further large scale multicenter epidemiological studies are warranted to confirm this finding and the molecular mechanism for the association need to be elucidated further.

Association between 8q24 (rs13281615 and rs6983267) polymorphism and breast cancer susceptibility: a meta-analysis involving 117,355 subjects

Published data on the association between 8q24 polymorphism and breast cancer (BC) risk are inconclusive. Thus, we conducted a meta-analysis to evaluate the relationship between 8q24 (rs13281615 and rs6983267) polymorphism and BC risk. We searched PubMed, EMBASE, Web of Science and the Cochrane Library up to August 13, 2015 for relevant studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the strength of associations. Twenty-six studies published from 2008 to 2014, with a total of 52,683 cases and 64,672 controls, were included in this meta-analysis. The pooled results showed that there was significant association between 8q24 rs13281615 polymorphism and BC risk in any genetic model. In the subgroup analysis by ethnicity, the effects remained in Asians and Caucasians. However, no genetic models reached statistical association in Africans. There was no association in any genetic model in rs6983267. This meta-analysis suggests that 8q24 rs13281615 polymorphism is a risk factor for susceptibility to BC in Asians, Caucasians and in overall population, While, there was no association in Africans. The rs6983267 polymorphism has no association with BC risk in any genetic model. Further large scale multicenter epidemiological studies are warranted to confirm this finding.

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.

Establishing and characterizing patient-derived xenografts using pre-chemotherapy percutaneous biopsy and post-chemotherapy surgical samples from a prospective neoadjuvant breast cancer study

Background

Patient-derived xenografts (PDXs) are increasingly used in cancer research as a tool to inform cancer biology and drug response. Most available breast cancer PDXs have been generated in the metastatic setting. However, in the setting of operable breast cancer, PDX models both sensitive and resistant to chemotherapy are needed for drug development and prospective data are lacking regarding the clinical and molecular characteristics associated with PDX take rate in this setting.

Methods

The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant chemotherapy (NAC) trial of stage I-III breast cancer patients treated with neoadjuvant weekly taxane+/-trastuzumab followed by anthracycline-based chemotherapy. Using percutaneous tumor biopsies (PTB), we established and characterized PDXs from both primary (untreated) and residual (treated) tumors. Tumor take rate was defined as percent of patients with the development of at least one stably transplantable (passed at least for four generations) xenograft that was pathologically confirmed as breast cancer.

Results

Baseline PTB samples from 113 women were implanted with an overall take rate of 27.4% (31/113). By clinical subtype, the take rate was 51.3% (20/39) in triple negative (TN) breast cancer, 26.5% (9/34) in HER2+, 5.0% (2/40) in luminal B and 0% (0/3) in luminal A. The take rate for those with pCR did not differ from those with residual disease in TN (p = 0.999) and HER2+ (p = 0.2401) tumors. The xenografts from 28 of these 31 patients were such that at least one of the xenografts generated had the same molecular subtype as the patient. Among the 35 patients with residual tumor after NAC adequate for implantation, the take rate was 17.1%. PDX response to paclitaxel mirrored the patients’ clinical response in all eight PDX tested.

Conclusions

The generation of PDX models both sensitive and resistant to standard NAC is feasible and these models exhibit similar biological and drug response characteristics as the patients’ primary tumors. Taken together, these models may be useful for biomarker discovery and future drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0920-8) contains supplementary material, which is available to authorized users.

Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) is a membrane-spanning tyrosine kinase that mediates signaling for FGFs. Recent studies detected various point mutations of FGFR2 in multiple types of cancers, including breast cancer, lung cancer, gastric cancer, uterine cancer and ovarian cancer, yet the casual relationship between these mutations and tumorigenesis is unclear. Here we will discuss possible interactions between FGFR2 signaling and several major pathways through which the aberrantly activated FGFR2 signaling may result in breast cancer development. We will also discuss some recent developments in the discovery and application of therapies and strategies for breast cancers by inhibiting FGFR2 activities.

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code

Triple-negative (TN) breast cancer (BC) patients have limited treatment options and poor prognosis even after extant treatments and standard chemotherapeutic regimens. Linking TN patients to clinically known phenotypes with appropriate treatments is vital. Location-specific sequence variants are expected to be useful for this purpose by identifying subgroups within a disease population. Single gene mutational signatures have been widely reported, with related phenotypes in literature. We thoroughly survey currently available mutations (and mutated genes), linked to BC phenotypes, to demonstrate their limited performance as sole predictors/biomarkers to assign phenotypes to patients. We then explore mutational combinations, as a pilot study, using The Cancer Genome Atlas Research Network mutational data of BC and three machine learning methods: association rules (limitless arity multiple procedure), decision tree and hierarchical disjoint clustering. The study results in a patient classification scheme through combinatorial mutations in Phosphatidylinositol-4,5-Bisphosphate 3-Kinase and tumor protein 53, being consistent with all three methods, implying its validity from a diverse viewpoint. However, it would warrant further research to select multi-gene signatures to identify phenotypes specifically and be clinically used routinely.

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods

INTRODUCTION

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients.

METHODS

This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation.

RESULTS

The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics.

CONCLUSION

Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Genetic Breast Cancer Susceptibility Variants and Prognosis in the Prospectively Randomized SUCCESS A Study

Large-scale genotyping studies have identified over 70 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. However, knowledge regarding genetic risk factors associated with the prognosis is limited. The aim of this study was therefore to investigate the prognostic effect of nine known breast cancer risk SNPs. BC patients (n = 1687) randomly sampled in an adjuvant, randomized phase III trial (SUCCESS A study) were genotyped for nine BC risk SNPs: rs17468277 (CASP8) , rs2981582 (FGFR2) , rs13281615(8q24), rs3817198 (LSP1) , rs889312 (MAP3K1) , rs3803662 (TOX3) , rs13387042(2q35), rs4973768 (SLC4A7) , rs6504950 (COX11) . Cox proportional hazards models were used to test the SNPs' association with overall survival (OS) and progression-free survival (PFS). Additional analyses were carried out for molecular subgroups. rs3817198 in LSP1 (lymphocyte-specific protein 1) was the only SNP that significantly influenced OS (p = 0.01) and PFS (p < 0.01) in the likelihood ratio test comparing the genetic survival model with the clinical survival model. In the molecular subgroups, triple-negative patients with two minor alleles in rs3817198 had a much better prognosis relative to OS (adjusted HR 0.03; 95% CI 0.002 - 0.279) and PFS (HR 0.09; 95% CI 0.02 - 0.36) than patients with the common alleles. The same effect on PFS was shown for patients with luminal A tumors (HR 0.19; 95% CI 0.05 - 0.84), whereas patients with luminal B tumors had a poorer PFS with two minor alleles (HR 2.13; 95% CI 1.02 - 4.40). The variant in rs3817198 has a prognostic effect particularly in the subgroup of patients with triple-negative BC, suggesting a possible link with immunomodulation and BC.

Fibroblast growth factor receptors in breast cancer

Fibroblast growth factor receptors are growth factor receptor tyrosine kinases, exerting their roles in embryogenesis, tissue homeostasis, and development of breast cancer. Recent genetic studies have identified some subtypes of fibroblast growth factor receptors as strong genetic loci associated with breast cancer. In this article, we review the recent epidemiological findings and experiment results of fibroblast growth factor receptors in breast cancer. First, we summarized the structure and physiological function of fibroblast growth factor receptors in humans. Then, we discussed the common genetic variations in fibroblast growth factor receptors that affect breast cancer risk. In addition, we also introduced the potential roles of each fibroblast growth factor receptors isoform in breast cancer. Finally, we explored the potential therapeutics targeting fibroblast growth factor receptors for breast cancer. Based on the biological mechanisms of fibroblast growth factor receptors leading to the pathogenesis in breast cancer, targeting fibroblast growth factor receptors may provide new opportunities for breast cancer therapeutic strategies.

Myiasis associated with an invasive ductal carcinoma of the left breast: case study

Most breast cancers originate in the ductal epithelium and are referred to as invasive ductal carcinoma. In this study we report on the clinical procedures adopted to diagnose myiasis in association with infiltrating metastatic breast carcinoma in a female patient. A 41 years old woman came to the Federal Hospital of Andaraí complaining of intense itching, warmth, redness and hardening of the breast, which had acquired the aspect of an orange peel. A lesion in the left breast was cavitated, dimpled, had fetid odor, and had fibrotic and infected air nodules filled with exudate and Dipteran larvae. The tissue was cleaned and 33 larvae were extracted. The patient was hospitalized and received Ivermectin. Eighteen of the larvae extracted from the patient were placed in 70% alcohol, and twelve were placed in a container with sterile wood shavings under controlled conditions until they metamorphosed into adults. The taxonomic identification of the flies revealed that the culprit was Cochliomyia hominivorax. A histopathological exam conducted three months earlier had revealed infiltrating ductal carcinoma. Two months after the myiasis treatment, the breast tissue had healed. The patient had waited ten days from the onset of the myiasis to seek treatment, and that delay interfered negatively in the prognosis of both the neoplasm and the myiasis. This study is relevant to public health in view of the strong social impact of myiasis.

Association Study Confirmed Three Breast Cancer-Specific Molecular Subtype-Associated Susceptibility Loci in Chinese Han Women

BACKGROUND

Breast cancer is a heterogeneous and polygenic disease that can be divided into different molecular subtypes based on histological and genomic features. To date, numerous susceptibility loci of breast cancer have been discovered by genome-wide association studies and may expand the genetic features. However, few loci have been further studied according to molecular subtypes.

MATERIALS AND METHODS

We genotyped 23 recently discovered single nucleotide polymorphisms using the Sequenom iPLEX platform in a female Chinese cohort of 3,036 breast cancer patients (2,935 samples matched molecular subtypes) and 3,036 healthy controls.

RESULTS

Through a stratification analysis, 5q11.2/MAP3K1 (rs16886034, rs16886364, rs16886397, rs1017226, rs16886448) and 7q32.3/LINC-PINT (rs4593472) were associated with Luminal A, and 10q26.1/FGFR2 (rs35054928) was associated with Luminal B.

CONCLUSION

In our study, breast cancer-specific molecular subtype-associated susceptibility loci were confirmed in Chinese Han women, which contributes to a better genetic understanding of breast cancer in different molecular subtypes.

IMPLICATIONS FOR PRACTICE

To date, genome-wide association studies have identified more than 90 susceptibility loci associated with breast cancer. However, few loci have been further studied according to molecular subtype. The results of this study are that breast cancer-specific molecular subtype-associated susceptibility loci were confirmed in Chinese Han women, which contributes to a better genetic understanding of breast cancer in different molecular subtypes.

Antiproliferative and apoptotic effects of a specific anti-insulin-like growth factor I receptor single chain antibody on breast cancer cells

Insulin-like growth factor I receptor (IGF-IR) is expressed on breast cancer cells and involves in metastasis, survival, and proliferation. Currently, application of IGF-IR-targeting monoclonal antibodies (mAbs), alone or in combination with other drugs, is a promising strategy for breast cancer therapy. Single-chain fragment variable (scFv) antibodies have been introduced as appropriate tools for tumor-targeting purposes because of their advantages over whole antibodies. In the present study, we employed a naïve phage library and isolated scFvs against a specific epitope from extracellular domain of IGF-IR by panning process. The selected scFvs were further characterized using polyclonal and monoclonal phage ELISA, soluble monoclonal ELISA, and colony PCR and sequencing. Antiproliferative and apoptotic effects of selected scFv antibodies on breast cancer cell lines were also evaluated by MTT and Annexin V/PI assays. The results of ELISA indicated specific reactions of the isolated scFvs against the IGF-IR peptide, and analyses of PCR product and sequencing confirmed the presence of full length V_H and Vκ inserts. Treatment of MCF7 and SKBR3 cells with anti-IGF-IR scFv led to a significant growth inhibition. The results also showed that scFv treatment significantly augmented trastuzumab growth inhibitory effects on SKBR3 cells. The percentage of the apoptotic MCF7 and SKBR3 cells after 24-h treatment with scFv was 39 and 30.70 %, respectively. Twenty-four-hour treatment with scFv in combination with trastuzumab resulted in 44.75 % apoptosis of SKBR3 cells. Taken together, our results demonstrate that the targeting of IGF-IR by scFv can be an effective strategy in the treatment of breast cancer and provide further evidence for effectiveness of dual targeting of HER2 and IGF-IR in breast cancer therapy.

Comparing Quantitative Immunohistochemical Markers of Angiogenesis to Contrast-Enhanced Subharmonic Imaging

OBJECTIVES

Different methods for obtaining tumor neovascularity parameters based on immunohistochemical markers were compared to contrast-enhanced subharmonic imaging (SHI).

METHODS

Eighty-five athymic nude female rats were implanted with 5 × 10(6) breast cancer cells (MDA-MB-231) in the mammary fat pad. The contrast agent Definity (Lantheus Medical Imaging, North Billerica, MA) was injected, and SHI was performed using a modified Sonix RP scanner (Analogic Ultrasound, Richmond, British Columbia, Canada) with a L9-4 linear array (transmitting/receiving frequencies, 8/4 MHz). Afterward, specimens were stained for endothelial cells (CD31), vascular endothelial growth factor (VEGF), and cyclooxygenase 2 (COX-2). Tumor neovascularity was assessed in 4 different ways using a histomorphometry system (×100 magnification: (1) over the entire tumor; (2) in small sub-regions of interest (ROIs); (3) in the tumor periphery and centrally; and (4) in 3 regions of maximum marker expression (so-called hot spots). Results from specimens and from SHI were compared by linear regression.

RESULTS

Fifty-four rats (64%) showed tumor growth, and 38 were successfully imaged. Subharmonic imaging depicted the tortuous morphologic characteristics of tumor neovessels and delineated small areas of necrosis. The immunohistochemical markers did not correlate with SHI measures over the entire tumor area or over small sub-ROIs (P > .18). However, when the specimens were subdivided into central and peripheral regions, COX-2 and VEGF correlated with SHI in the periphery (r = -0.42; P = .005; and r = -0.32; P = .049, respectively).

CONCLUSIONS

When comparing quantitative contrast measures of tumor neovascularity to immunohistochemical markers of angiogenesis in xenograft models, ROIs corresponding to the biologically active region should be used to account for tumor heterogeneity.

Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies

Background

A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples.

Methods

We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data.

Results

The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (<7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification.

Conclusions

We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed that incorporation of scan-level features have the potential to lead to more accurate purification results by alleviating the loss in information as a result of integrating peaks. We believe cancer biomarker discovery studies that use mass spectrometric analysis of human biospecimens can greatly benefit from topic model-based purification of the data prior to statistical and pathway analyses.

Genetic variants in FGFR2 and TNRC9 genes are associated with breast cancer risk in Pakistani women

Single nucleotide polymorphisms (SNPs) lead to genetic differences in breast cancer (BC) susceptibility among women from different ethnicities. The present study aimed at investigating the involvement of SNPs of three genes, including fibroblast growth factor receptor 2 (FGFR2), trinucleotide-repeat-containing 9 (TNRC9) and mitogen-activated protein kinase kinase kinase 1 (MAP3K1), as risk factors for the development of BC. A case‑control study (90‑100 cases; 90‑100 controls) was performed to evaluate five genetic variants of three genes, including FGFR2 (SNPs: rs1219648, rs2981582), TNRC9 (SNPs: rs8051542, rs3803662) and MAP3K1 (SNP: rs889312) as BC risk factors in Pakistani women. Significant associations were observed between BC risk and two SNPs of FGFR2 [rs2981582 (P=0.005), rs1219648 (P=9.08e‑006)] and one SNP of TNRC9 [rs3803662) (P=0.012)] in Pakistani women. On examining the different interactions of these SNPs with various clinicopathological characteristics, all three associated genetic variants, rs2981582 rs1219648 and rs3803662, exhibited a greater predisposition to sporadic, in comparison to familial, BC. Furthermore, there was an increased effect of BC risk between haplotype combinations of the two SNPs of FGFR2 (rs2981582 and rs1219648) in Pakistani women. The results of the present study suggest that variants of FGFR2 and TNRC9 may contribute to the genetic susceptibility of BC in Pakistani women.

FGFR2 risk SNPs confer breast cancer risk by augmenting oestrogen responsiveness

The fibroblast growth factor receptor 2 (FGFR2) locus is consistently the top hit in genome-wide association studies for oestrogen receptor-positive (ER(+)) breast cancer. Yet, its mode of action continues to be controversial. Here, we employ a systems biology approach to demonstrate that signalling via FGFR2 counteracts cell activation by oestrogen. In the presence of oestrogen, the oestrogen receptor (ESR1) regulon (set of ESR1 target genes) is in an active state. However, signalling by FGFR2 is able to reverse the activity of the ESR1 regulon. This effect is seen in multiple distinct FGFR2 signalling model systems, across multiple cells lines and is dependent on the presence of FGFR2. Increased oestrogen exposure has long been associated with an increased risk of breast cancer. We therefore hypothesized that risk variants should reduce FGFR2 expression and subsequent signalling. Indeed, transient transfection experiments assaying the three independent variants of the FGFR2 risk locus (rs2981578, rs35054928 and rs45631563) in their normal chromosomal context show that these single-nucleotide polymorphisms (SNPs) map to transcriptional silencer elements and that, compared with wild type, the risk alleles augment silencer activity. The presence of risk variants results in lower FGFR2 expression and increased oestrogen responsiveness. We thus propose a molecular mechanism by which FGFR2 can confer increased breast cancer risk that is consistent with oestrogen exposure as a major driver of breast cancer risk. Our findings may have implications for the clinical use of FGFR2 inhibitors.

The insulin-like growth factor-I receptor (IGF-IR) in breast cancer: biology and treatment strategies

Breast cancer is the most common cancer and the second leading cause of cancer-related deaths among women worldwide. Although patients are often diagnosed in the early and curable stages, the treatment of metastatic breast cancer remains a major clinical challenge. The combination of chemotherapy with new targeting agents, such as bevacizumab, is helpful in improving patient survival; however, novel treatment strategies are required to improve clinical outcomes. The insulin-like growth factor-I receptor (IGF-IR) is a tyrosine kinase cell surface receptor which is involved in the regulation of cell growth and metabolism. Previous studies have shown that activation of the IGF-IR signaling pathway promotes proliferation, survival, and metastasis of breast cancer cells. Additionally, overexpression of IGF-IR is associated with breast cancer cell resistance to anticancer therapies. Recently, IGF-IR has been introduced as a marker of stemness in breast cancer cells and there is also accumulating evidence that IGF-IR contributes to the establishment and maintenance of breast cancer epithelial-mesenchymal transition (EMT). Therefore, pharmacological or molecular targeting of IGF-IR could be a promising strategy, in the treatment of patients with breast cancer, particularly in order to circumvent the therapeutic resistance and targeting breast cancer stem/progenitors. Currently, many strategies have been developed for targeting IGF-IR, some have entered clinical trials and some are in preclinical stages for breast cancer therapy. In this review, we will first discuss on the biology of IGF-IR in an attempt to find the role of this receptor in breast cancer and then discuss about therapeutic strategies to target this receptor.