Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes

A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study

Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mendelian randomization to examine associations between metabolic traits and breast cancer outcomes. In the Pathways Study of 3,902 patients and a median follow-up time of 10.5 years, we adapted a Mendelian randomization approach to calculate PGS for 55 metabolic traits and tested their associations with seven survival outcomes. Multivariable Cox proportional hazards models were used to derive HRs and 95% confidence intervals (CI) with adjustment for covariates. The highest tertile (T3) of PGS for cardiovascular disease was associated with shorter overall survival (HR = 1.34, 95% CI = 1.11-1.61) and second primary cancer-free survival (HR = 1.31, 95% CI = 1.12-1.53). PGS for hypertension (T3) was associated with shorter overall survival (HR = 1.20, 95% CI = 1.00-1.43), second primary cancer-free survival (HR = 1.24, 95% CI = 1.06-1.45), invasive disease-free survival (HR = 1.18, 95% CI = 1.01-1.38), and disease-free survival (HR = 1.21, 95% CI = 1.04-1.39). PGS for serum cystatin C levels (T3) was associated with longer disease-free survival (HR = 0.82, 95% CI = 0.71-0.95), breast event-free survival (HR = 0.74, 95% CI = 0.61-0.91), and breast cancer-specific survival (HR = 0.72, 95% CI = 0.54-0.95). The above associations were significant at a nominal P < 0.05 level but not after correcting for multiple testing (Bonferroni P < 0.0009). Our analyses revealed notable associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with breast cancer survival outcomes. These findings implicate metabolic traits in breast cancer prognosis.

Significance

To our knowledge, this is the largest study of PGS for metabolic traits with breast cancer prognosis. The findings revealed significant associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with several breast cancer survival outcomes. These findings implicate an underappreciated role of metabolic traits in breast cancer prognosis that would warrant further exploration.

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.

UACA locus is associated with breast cancer chemoresistance and survival

Few germline genetic variants have been robustly linked with breast cancer outcomes. We conducted trans-ethnic meta genome-wide association study (GWAS) of overall survival (OS) in 3973 breast cancer patients from the Pathways Study, one of the largest prospective breast cancer survivor cohorts. A locus spanning the UACA gene, a key regulator of tumor suppressor Par-4, was associated with OS in patients taking Par-4 dependent chemotherapies, including anthracyclines and anti-HER2 therapy, at a genome-wide significance level (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.27 \times 10^{ - 9}$$\end{document}P=1.27×10−9). This association was confirmed in meta-analysis across four independent prospective breast cancer cohorts (combined hazard ratio = 1.84, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.28 \times 10^{ - 11}$$\end{document}P=1.28×10−11). Transcriptome-wide association study revealed higher UACA gene expression was significantly associated with worse OS (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 4.68 \times 10^{ - 7}$$\end{document}P=4.68×10−7). Our study identified the UACA locus as a genetic predictor of patient outcome following treatment with anthracyclines and/or anti-HER2 therapy, which may have clinical utility in formulating appropriate treatment strategies for breast cancer patients based on their genetic makeup.

A functional variant near XCL1 gene improves breast cancer survival via promoting cancer immunity

Most genome-wide association studies (GWASs) identify genetic variants for breast cancer occurrence. In contrast, few are for recurrence and mortality. We conducted a GWAS on breast cancer survival after diagnosis in estrogen receptor-positive patients, including 953 Taiwanese patients with 159 events. Through Cox proportional hazard models estimation, we identified 24 risk SNPs with p < 1 × 10^-5 . Based on imputation and integrated analysis, one SNP, rs1024176 (located in 1q24.2, p = 2.43 × 10^-5 ) was found to be a functional variant associated with breast cancer survival and XCL1 gene expression. A series of experimental approaches, including cell-based analyses and CRISPR/Cas9 genome-editing system, were then used and identified the transcription factor MYBL2 was able to discriminately bind to the A allele of rs1024176, the protective variant for breast cancer survival, which promoted XCL1 expression, but not to the G allele of rs1024176. The chemokine XCL1 attracts type 1 dendritic cells (DC1s) to the tumor microenvironment. In breast cancer tissues, we applied a two-step Mendelian randomization analysis, using expression quantitative trait loci as instrumental variables, to confirm higher XCL1 expression was correlated with higher DC1 signatures and favorable disease progression, through the causal effect of rs1024176-A allele. Our study supports the genetic effect on preventing breast cancer survival through XCL1-induced DC1 recruitment in tumor microenvironment.

Use of clinical nomograms for predicting survival outcomes in young women with breast cancer

Early-onset breast cancer (BC) has been recognized to be more aggressive compared with its later counterparts. Survival models of BC in young patients have rarely been reported in previous studies. The current study aimed to establish and validate prediction models with clinicopathological variables for visceral metastasis-free survival (VFS), disease-free-survival (DFS) and overall survival (OS) time in young patients with BC. Clinicopathological data were obtained for 351 patients with primary breast tumors who were ≤40 years old. Univariate and multivariate analyses were performed and nomograms were established to screen and illustrate the prognostic factors. Risk scores were calculated based on coefficients from the Cox regression analysis. Internal validation of the prediction models was conducted by predicting the prognosis of cases randomly sampled from the cohort used in the current study. Multivariate analysis demonstrated that N stage (P=0.004), molecular subtype (P=0.007) and age (P=0.005) were significant independent prognostic factors for VFS. Similarly, N stage (P=0.002) and molecular subtype (P=0.001) were significantly associated with DFS. In addition, N stage (P=0.006), molecular subtype (P=0.006) and the presence of an initially inoperable tumor (P=0.005) were significant independent prognostic factors for OS. According to the Cox regression analysis, nomograms were generated to illustrate the effect of independent prognostic factors on VFS, DFS and OS. Risk scores were calculated and internal validation demonstrated the reliability of the prediction models. In conclusion, N stage and molecular subtype were identified as predictors for VFS, DFS and OS in early-onset BC. Furthermore, an age of <35 years at diagnosis was revealed to be unfavorable for VFS and the presence of an initially inoperable tumor was identified to reduce OS time.

Subtype-specific associations between breast cancer risk polymorphisms and the survival of early-stage breast cancer

BACKGROUND

Limited evidence suggests that inherited predisposing risk variants might affect the disease outcome. In this study, we analyzed the effect of genome-wide association studies-identified breast cancer-risk single nucleotide polymorphisms on survival of early-stage breast cancer patients in a Chinese population.

METHODS

This retrospective study investigated the relationship between 21 GWAS-identified breast cancer-risk single nucleotide polymorphisms and the outcome of 1177 early stage breast cancer patients with a long median follow-up time of 174 months. Cox proportional hazards regression models were used to estimate the hazard ratios and their 95% confidence intervals. Primary endpoints were breast cancer special survival and overall survival while secondary endpoints were invasive disease free survival and distant disease free survival.

RESULTS

Multivariate survival analysis showed only the rs2046210 GA genotype significantly decreased the risk of recurrence and death for early stage breast cancer. After grouping breast cancer subtypes, significantly reduced survival was associated with the variant alleles of rs9485372 for luminal A and rs4415084 for triple negative breast cancer. Importantly, all three single-nucleotide polymorphisms, rs889312, rs4951011 and rs9485372 had remarkable effects on survival of luminal B EBC, either individually or synergistically. Furthermore, statistically significant multiplicative interactions were found between rs4415084 and age at diagnosis and between rs3803662 and tumor grade.

CONCLUSIONS

Our results demonstrate that breast cancer risk susceptibility loci identified by GWAS may influence the outcome of early stage breast cancer patients' depending on intrinsic tumor subtypes in Chinese women.

Revisiting Neutrophil Gelatinase-Associated Lipocalin (NGAL) in Cancer: Saint or Sinner?

Human neutrophil gelatinase-associated lipocalin (NGAL) is a glycoprotein present in a wide variety of tissues and cell types. NGAL exists as a 25 kDa monomer, a 46 kDa homodimer (the most abundant form in healthy subjects) and a 130 kDa disulfide-linked heterodimer bound to latent matrix metalloproteinase-9. Dysregulated expression of NGAL in human malignancies suggests its value as a clinical marker. A growing body of evidence is highlighting NGAL’s paradoxical (i.e., both beneficial and detrimental) effects on cellular processes associated with tumor development (proliferation, survival, migration, invasion, and multidrug resistance). At least two distinct cell surface receptors are identified for NGAL. This review (i) summarizes our current knowledge of NGAL’s expression profiles in solid tumors and leukemias, and (ii) critically evaluates the beneficial and detrimental activities of NGAL having been documented in a diverse range of cancer-derived cell lines. A better understanding of the causal relationships between NGAL dysregulation and tumor development will require a fine analysis of the molecular aspects and biological role(s) of NGAL both in primary tumors and at different stages of disease. Having an accurate picture of NGAL’s contribution to tumor progression is a prerequisite for attempting to modulate this protein as a putative therapeutic target.

Associations between genetic polymorphisms of membrane transporter genes and prognosis after chemotherapy: meta-analysis and finding from Seoul Breast Cancer Study (SEBCS)

Membrane transporters can be major determinants of the pharmacokinetic profiles of anticancer drugs. The associations between genetic variations of ATP-binding cassette (ABC) and solute carrier (SLC) genes and cancer survival were investigated through a meta-analysis and an association study in the Seoul Breast Cancer Study (SEBCS). Including the SEBCS, the meta-analysis was conducted among 38 studies of genetic variations of transporters on various cancer survivors. The population of SEBCS consisted of 1338 breast cancer patients who had been treated with adjuvant chemotherapy. A total of 7750 SNPs were selected from 453 ABC and/or SLC genes typed by an Affymetrix 6.0 chip. ABCB1 rs1045642 was associated with poor progression-free survival in a meta-analysis (HR = 1.33, 95% CI: 1.07-1.64). ABCB1, SLC8A1, and SLC12A8 were associated with breast cancer survival in SEBCS (P_gene < 0.05). ABCB1 rs1202172 was differentially associated with survival depending on the chemotherapy (P_interaction = 0.035). Our finding provides suggestive associations of membrane transporters on cancer survival.

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path.