Genetic variation at CYP3A is associated with age at menarche and breast cancer risk: a case-control study

The prognostic significance of human ovarian aging-related signature in breast cancer after surgery: A multicohort study

Background

Recent studies have shown that ovarian aging is strongly associated with the risk of breast cancer, however, its prognostic impact on breast cancer is not yet fully understood. In this study, we performed a multicohort genetic analysis to explore its prognostic value and biological features in breast cancer.

Methods

The gene expression and clinicopathological data of 3366 patients from the The Cancer Genome Atlas (TCGA) cohort, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and the GSE86166 cohort were analyzed. A total of 290 ovarian aging-related genes (OARGs) were included in the establishment of the prognostic model. Furthermore, functional mechanisms analysis, drug sensitivity, and immune cell infiltration were investigated using bioinformatic methods.

Results

An eight OARG-based signature was established and validated using independent cohorts. Two risk subgroups of patients with distinct survival outcomes were identified by the OARG-based signature. A nomogram with good predictive performance was developed by integrating the OARG risk score with clinicopathological factors. Moreover, the OARG-based signature was correlated with DNA damage repair, immune cell signaling pathways, and immunomodulatory functions. The patients in the low-risk subgroup were found to be sensitive to traditional chemotherapeutic, endocrine, and targeted agents (doxorubicin, tamoxifen, lapatinib, etc.) and some novel targeted drugs (sunitinib, pazopanib, etc.). Moreover, patients in the low-risk subgroup may be more susceptible to immune escape and therefore respond less effectively to immunotherapy.

Conclusions

In this study, we proposed a comprehensive analytical method for breast cancer assessment based on OARG expression patterns, which could precisely predict clinical outcomes and drug sensitivity of breast cancer patients.

Fucoxanthin Is a Potential Therapeutic Agent for the Treatment of Breast Cancer

Breast cancer (BC) is one of the most common cancers diagnosed and the leading cause of cancer-related death in women. Although there are first-line treatments for BC, drug resistances and adverse events have been reported. Given the incidence of BC keeps increasing, seeking novel therapeutics is urgently needed. Fucoxanthin (Fx) is a dietary carotenoid commonly found in seaweeds and diatoms. Both in vitro and in vivo studies show that Fx and its deacetylated metabolite fucoxanthinol (Fxol) inhibit and prevent BC growth. The NF-κB signaling pathway is considered the major pathway contributing to the anti-proliferation, anti-angiogenesis and pro-apoptotic effects of Fx and Fxol. Other signaling molecules such as MAPK, MMP2/9, CYP and ROS are also involved in the anti-cancer effects by regulating the tumor microenvironment, cancer metastasis, carcinogen metabolism and oxidation. Besides, Fx also possesses anti-obesity effects by regulating UCP1 levels and lipid metabolism, which may help to reduce BC risk. More importantly, mounting evidence demonstrates that Fx overcomes drug resistance. This review aims to give an updated summary of the anti-cancer effects of Fx and summarize the underlying mechanisms of action, which will provide novel strategies for the development of Fx as an anti-cancer therapeutic agent.

The influence of CYP2C19*2 and CYP3A5*3 variants on the development of depression and effectiveness of therapy: A preliminary study

The most common mental illness is depression; however, its pathogenesis is not fully understood. One of the factors that may influence its development and the effectiveness of therapy are the cytochromes of the p450 complex. CYP3A5 and CYP2C19 are involved in the metabolism of drugs used in the treatment of depression. These cytochromes can also generate reactive oxygen species, which are known to participate in the pathogenesis of depression. The aim of the study was to determine the frequency of CYP3A5*3 and CYP2C19*2 variants among a group of patients with depression to identify any potential association with disease development and progression, and the effectiveness of pharmacotherapy. A group of 103 patients suffering from recurrent depressive disorder and another of 93 healthy individuals were investigated using RFLP. It was found that the CYP3A5*3 allele may have a protective role in the development of depression (p = 0.0036). Heterozygous CYP3A5*1/*3 was more common in controls than the patients (p = 0.0300). Homozygotes were associated with an earlier onset than heterozygotes (p = 0.0292). For CYP2C19, patients with at least one CYP2C19*2 allele revealed better treatment results expressed as percentage change in Hamilton Depression Rating Scale (p = 0.0239). The identification of CYP3A5 and CYP2C19 allelic variants may be useful when assessing the effectiveness of pharmacotherapy.

Cytochrome P450: Implications for human breast cancer

The treatment options for breast cancer include endocrine therapy, targeted therapy and chemotherapy. However, some patients with triple-negative breast cancer cannot benefit from these methods. Therefore, novel therapeutic targets should be developed. The cytochrome P450 enzyme (CYP) is a crucial metabolic oxidase, which is involved in the metabolism of endogenous and exogenous substances in the human body. Some products undergoing the metabolic pathway of the CYP enzyme, such as hydroxylated polychlorinated biphenyls and 4-chlorobiphenyl, are toxic to humans and are considered to be potential carcinogens. As a class of multi-gene superfamily enzymes, the subtypes of CYPs are selectively expressed in breast cancer tissues, especially in the basal-like type. In addition, CYPs are essential for the activation or inactivation of anticancer drugs. The association between CYP expression and cancer risk, tumorigenesis, progression, metastasis and prognosis has been widely reported in basic and clinical studies. The present review describes the current findings regarding the importance of exploring metabolic pathways of CYPs and gene polymorphisms for the development of vital therapeutic targets for breast cancer.

Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10-3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10-4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

Association of breast cancer risk with polymorphisms in genes involved in the metabolism of xenobiotics and interaction with tobacco smoking: A gene-set analysis

Single nucleotide polymorphisms (SNPs) in genes involved in xenobiotics metabolism (XM) are suspected to play a role in breast cancer risk. However, previous findings based on a SNP by SNP approach need to be replicated taking into account the combined effects of multiple SNPs. We used a gene-set analysis method to study the association between breast cancer risk and genetic variation in XM genes (seen as a set of SNPs) and in the XM pathway (seen as a set of genes). We also studied the interaction between variants in XM genes and tobacco smoking. The analysis was conducted in a case-control study of 1,125 cases and 1,172 controls. Using a dedicated chip, genotyping data of 585 SNPs in 68 XM genes were available. Genetic variation in the whole XM pathway was significantly associated with premenopausal breast cancer risk (p = 0.008). This association was mainly driven by genetic variation in NAT2, CYP2C18, CYP2C19, AKR1C2 and ALDH1A3. The association between the XM gene pathway and breast cancer was observed among current and previous smokers, but not among never smokers (p = 0.013 for interaction between XM genes and tobacco smoking status). The association with breast cancer risk indicates that XM genes variants may play a role in breast carcinogenesis through their detoxification function of environmental pollutants, such as those contained in tobacco smoke.

Links between age at menarche, antral follicle count, and body mass index in African American and European American women

OBJECTIVE

To examine the relationships between age at menarche, antral follicle count (AFC), and body mass index (BMI) in a multi-ethnic population of women.

DESIGN

Community-based, cross-sectional study.

SETTING

Academic setting.

PATIENT(S)

A total of 245 African American women and 273 European American women, aged 25-45 years, with regular menstrual cycles and no reproductive disorders. The ethnicity of these women was self-reported and genetically validated.

INTERVENTION(S)

The AFCs were measured by transvaginal ultrasound during the early follicular phase. Anthropometric measurements were taken, and age at menarche was gathered by questionnaire.

MAIN OUTCOME MEASURE(S)

Determination of the associations between age of menarche and adult AFC and BMI.

RESULT(S)

Earlier age of menarche was associated with both higher BMIs and higher AFCs in adulthood, with control for female age. The antral follicle difference between early (<12 years) vs. late (≥15 years) initiation of menarche in both white and black women was +3.81 and +3.34 follicles, respectively, which is equivalent to an approximately 20% difference in AFC.

CONCLUSION(S)

This study provides the first evidence that timing of menarche may influence AFC. Because of limited studies on African American women, this work provides additional needed data and may enhance our ability to prospectively screen and better treat various diseases associated with the female reproductive lifespan.

The prognostic value of differentially expressed CYP3A subfamily members for hepatocellular carcinoma

Objective

The activities of four cytochrome P3A (CYP3A) subfamily members (CYP3A4, CYP3A5, CYP3A7, and CYP3A43) are well documented in drug metabolism. However, the association between CYP3A subfamily members and hepatocellular carcinoma (HCC) remains unclear. This study investigated the prognostic value of CYP3A subfamily mRNA expression levels with HCC prognosis.

Materials and methods

Data from a total of 360 HCC patients were retrieved from The Cancer Genome Atlas database, and data from 231 HCC patients were retrieved from the Gene Expression Omnibus database. Kaplan–Meier analysis and Cox regression models were utilized to determine median survival, overall survival, and recurrence-free survival. Hazard ratios and 95% CI were calculated.

Results

Low expression of CYP3A4, CYP3A5, and CYP3A43 in the tumor tissue was associated with short median survival (crude p=0.004, 0.001, and 0.001; adjusted p=0.022, 0.005, and 0.013, respectively). Joint-effects combination analysis of CYP3A4, CYP3A5/CYP3A4, CYP3A43/CYP3A5, and CYP3A43 revealed that high expression groups of two genes (group C, group c, group 3) were associated with a reduced risk of death, as compared to low expression of two genes (group A, group a, group 1), and the adjusted p values were 0.001, 0.004, and 0.001, respectively. Joint-effects analysis of CYP3A4, CYP3A5, and CYP3A43 showed that groups III and IV had a reduced risk of death, as compared to group I (adjusted p=0.024 and 0.002, respectively).

Conclusion

CYP3A4, CYP3A5, and CYP3A43 mRNA expression levels are potential prognostic markers of HCC.

Genetic variations, reproductive aging, and breast cancer risk in African American and European American women: The Women's Circle of Health Study

Reproductive aging phenotypes, including age at menarche (AM) and age at natural menopause (ANM), are well-established risk factors for breast cancer. In recent years, many genetic variants have been identified in association with AM and ANM in genome-wide association studies among European populations. Using data from the Women’s Circle of Health Study (WCHS) of 1,307 European-American (EA) and 1,365 African-American (AA) breast cancer cases and controls, we aimed to replicate 53 earlier GWAS variants for AM and ANM in AA and EA groups and to perform analyses on total and net reproductive lifespan (TRLS; NRLS). Breast cancer risk was also examined in relation to a polygenic risk score (PRS) for each of the reproductive aging phenotypes. We replicated a number of variants in EA women, including rs7759938 in LIN28B for AM and rs16991615 in MCM8 for ANM; whereas in the AA group, only one SNP (rs2947411 in TMEM18) for AM was directionally consistent and nominally significant. In analysis of TRLS and NRLS, several SNPs were significant, including rs466639 in RXRG that was associated with both phenotypes in both AA and EA groups. None of the PRS was associated with breast cancer risk. Given the paucity of data available among AA populations, our study contributes to the literature of genetics of reproductive aging in AA women and highlights the importance of cross population replication of GWAS variants.

CYP3A7*1C allele is associated with reduced levels of 2-hydroxylation pathway oestrogen metabolites

Background:

Endogenous sex hormones are well-established risk factors for breast cancer; the contribution of specific oestrogen metabolites (EMs) and/or ratios of specific EMs is less clear. We have previously identified a CYP3A7*1C allele that is associated with lower urinary oestrone (E₁) levels in premenopausal women. The purpose of this analysis was to determine whether this allele was associated with specific pathway EMs.

Methods:

We measured successfully 12 EMs in mid-follicular phase urine samples from 30 CYP3A7*1C carriers and 30 non-carriers using HPLC-MS/MS.

Results:

In addition to having lower urinary E₁ levels, CYP3A7*1C carriers had significantly lower levels of four of the 2-hydroxylation pathway EMs that we measured (2-hydroxyestrone, P=1.1 × 10⁻¹²; 2-hydroxyestradiol, P=2.7 × 10⁻⁷; 2-methoxyestrone, P=1.9 × 10⁻¹²; and 2-methoxyestradiol, P=0.0009). By contrast, 16α-hydroxylation pathway EMs were slightly higher in carriers and significantly so for 17-epiestriol (P=0.002).

Conclusions:

The CYP3A7*1C allele is associated with a lower urinary E₁ levels, a more pronounced reduction in 2-hydroxylation pathway EMs and a lower ratio of 2-hydroxylation:16α-hydroxylation EMs in premenopausal women. To further characterise the association between parent oestrogens, EMs and subsequent risk of breast cancer, characterisation of additional genetic variants that influence oestrogen metabolism and large prospective studies of a broad spectrum of EMs will be required.

Discriminatory power of common genetic variants in personalized breast cancer diagnosis

Technology advances in genome-wide association studies (GWAS) has engendered optimism that we have entered a new age of precision medicine, in which the risk of breast cancer can be predicted on the basis of a person's genetic variants. The goal of this study is to evaluate the discriminatory power of common genetic variants in breast cancer risk estimation. We conducted a retrospective case-control study drawing from an existing personalized medicine data repository. We collected variables that predict breast cancer risk: 153 high-frequency/low-penetrance genetic variants, reflecting the state-of-the-art GWAS on breast cancer, mammography descriptors and BI-RADS assessment categories in the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We trained and tested naïve Bayes models by using these predictive variables. We generated ROC curves and used the area under the ROC curve (AUC) to quantify predictive performance. We found that genetic variants achieved comparable predictive performance to BI-RADS assessment categories in terms of AUC (0.650 vs. 0.659, p-value = 0.742), but significantly lower predictive performance than the combination of BI-RADS assessment categories and mammography descriptors (0.650 vs. 0.751, p-value < 0.001). A better understanding of relative predictive capability of genetic variants and mammography data may benefit clinicians and patients to make appropriate decisions about breast cancer screening, prevention, and treatment in the era of precision medicine.

Candidate gene-environment interactions in breast cancer

Gene-environment interactions have the potential to shed light on biological processes leading to disease, identify individuals for whom risk factors are most relevant, and improve the accuracy of epidemiological risk models. We review the progress that has been made in investigating gene-environment interactions in the field of breast cancer. Although several large-scale analyses have been carried out, only a few significant interactions have been reported. One of these, an interaction between CASP8-rs1045485 and alcohol consumption has been replicated, but others have not, including LSP1- rs3817198 and parity, and 1p11.2-rs11249433 and ever being parous. False positive interactions may arise if the gene and environment are correlated and the causal variant is less frequent than the tag SNP. We conclude that while much progress has been made in this area it is still too soon to tell whether gene-environment interactions will fulfil their promise. Before we can make this assessment we will need to replicate (or refute) the reported interactions, identify the causal variants that underlie tag-SNP associations and validate the next generation of epidemiological risk models.

Gene-environment dependence creates spurious gene-environment interaction

Gene-environment interactions have the potential to shed light on biological processes leading to disease and to improve the accuracy of epidemiological risk models. However, relatively few such interactions have yet been confirmed. In part this is because genetic markers such as tag SNPs are usually studied, rather than the causal variants themselves. Previous work has shown that this leads to substantial loss of power and increased sample size when gene and environment are independent. However, dependence between gene and environment can arise in several ways including mediation, pleiotropy, and confounding, and several examples of gene-environment interaction under gene-environment dependence have recently been published. Here we show that under gene-environment dependence, a statistical interaction can be present between a marker and environment even if there is no interaction between the causal variant and the environment. We give simple conditions under which there is no marker-environment interaction and note that they do not hold in general when there is gene-environment dependence. Furthermore, the gene-environment dependence applies to the causal variant and cannot be assessed from marker data. Gene-gene interactions are susceptible to the same problem if two causal variants are in linkage disequilibrium. In addition to existing concerns about mechanistic interpretations, we suggest further caution in reporting interactions for genetic markers.