Postmenopausal estrogen and progestin effects on the serum proteome

High serum levels of leucine-rich α-2 glycoprotein 1 (LRG-1) are associated with poor survival in patients with early breast cancer

BACKGROUND

Leucine-rich α-2 glycoprotein 1 (LRG-1) is a secreted glycoprotein that is mainly produced in the liver. Elevated levels of LRG-1 are found in a multitude of pathological conditions including eye diseases, diabetes, infections, autoimmune diseases, and cancer. In patients with early breast cancer (BC), high intratumoral LRG-1 protein expression levels are associated with reduced survival. In this study, we assessed serum levels of LRG-1 in patients with early BC and investigated its correlation with the presence of disseminated tumor cells (DTCs) in the bone marrow and survival outcomes.

METHODS

Serum LRG-1 levels of 509 BC patients were determined using ELISA and DTCs were assessed by immunocytochemistry using the pan-cytokeratin antibody A45-B/B3. We stratified LRG-1 levels according to selected clinical parameters. Using the log-rank (Mantel-Cox) test and multivariate Cox regression analysis, Kaplan-Meier survival curves and prognostic relevance were assessed.

RESULTS

Mean serum levels of LRG-1 were 29.70 ± 8.67 µg/ml. Age was positively correlated with LRG-1 expression (r = 0.19; p < 0.0001) and significantly higher LRG-1 levels were found in patients over 60 years compared to younger ones (30.49 ± 8.63 µg/ml vs. 28.85 ± 8.63 µg/ml; p = 0.011) and in postmenopausal patients compared to premenopausal patients (30.15 ± 8.34 µg/ml vs. 26.936.94 µg/ml; p = 0.002). Patients with no DTCs showed significantly elevated LRG-1 levels compared to the DTC-positive group (30.51 ± 8.69 µg/ml vs. 28.51 ± 8.54 µg/ml; p = 0.004). Overall and BC-specific survival was significantly lower in patients with high serum LRG-1 levels (above a cut-off of 33.63 µg/ml) compared to patients with lower LRG-1 levels during a mean follow-up of 8.5 years (24.8% vs. 11.1% BC-specific death; p = 0.0003; odds ratio 2.63, 95%CI: 1.56-4.36). Multivariate analyses revealed that LRG-1 is an independent prognostic marker for BC-specific survival (p = 0.001; hazard ratio 2.61).

CONCLUSIONS

This study highlights the potential of LRG-1 as an independent prognostic biomarker in patients with early BC.

An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next

Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.

Long-term changes in plasma proteomic profiles in premenopausal and postmenopausal Black and White women: the Atherosclerosis Risk in Communities study

OBJECTIVE

The activity, localization, and turnover of proteins within cells and plasma may contribute to physiologic changes during menopause and may influence disease occurrence. We examined cross-sectional differences and long-term changes in plasma proteins between premenopausal and naturally postmenopausal women.

METHODS

We used data from 4,508 (19% Black) women enrolled in the Atherosclerosis Risk in Communities study. SOMAscan multiplexed aptamer technology was used to measure 4,697 plasma proteins. Linear regression models were used to compare differences in proteins at baseline (1993-1995) and 18-year change in proteins from baseline to 2011-2013.

RESULTS

At baseline, 472 women reported being premenopausal and 4,036 women reported being postmenopausal, with average ages of 52.3 and 61.4 years, respectively. A greater proportion of postmenopausal women had diabetes (15 vs 9%), used hypertension (38 vs 27%) and lipid-lowering medications (10 vs 3%), and had elevated total cholesterol and waist girth. In multivariable adjusted models, 38 proteins differed significantly between premenopausal and postmenopausal women at baseline, with 29 of the proteins also showing significantly different changes between groups over the 18-year follow-up as the premenopausal women also reached menopause. These proteins were associated with various molecular/cellular functions (cellular development, growth, proliferation and maintenance), physiological system development (skeletal and muscular system development, and cardiovascular system development and function), and diseases/disorders (hematological and metabolic diseases and developmental disorders).

CONCLUSIONS

We observed significantly different changes between premenopausal and postmenopausal women in several plasma proteins that reflect many biological processes. These processes may help to understand disease development during the postmenopausal period.

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

Multimerin-1 and cancer: a review

Multimerin-1 (MMRN1) is a platelet protein with a role in haemostasis and coagulation. It is also present in endothelial cells (ECs) and the extracellular matrix (ECM), where it may be involved in cell adhesion, but its molecular functions and protein–protein interactions in these cellular locations have not been studied in detail yet. In recent years, MMRN1 has been identified as a differentially expressed gene (DEG) in various cancers and it has been proposed as a possible cancer biomarker. Some evidence suggest that MMRN1 expression is regulated by methylation, protein interactions, and non-coding RNAs (ncRNAs) in different cancers. This raises the questions if a functional role of MMRN1 is being targeted during cancer development, and if MMRN1’s differential expression pattern correlates with cancer progression. As a result, it is timely to review the current state of what is known about MMRN1 to help inform future research into MMRN1’s molecular mechanisms in cancer.

Dual-Outcome Intention-to-Treat Analyses in the Women's Health Initiative Randomized Controlled Hormone Therapy Trials

Dual-outcome intention-to-treat hazard rate analyses have potential to complement single-outcome analyses for the evaluation of treatments or exposures in relation to multivariate time-to-response outcomes. Here we consider pairs formed from important clinical outcomes to obtain further insight into influences of menopausal hormone therapy on chronic disease. As part of the Women's Health Initiative, randomized, placebo-controlled hormone therapy trials of conjugated equine estrogens (CEE) among posthysterectomy participants and of these same estrogens plus medroxyprogesterone acetate (MPA) among participants with an intact uterus were carried out at 40 US clinical centers (1993-2016). These data provide the context for analyses covering the trial intervention periods and a nearly 20-year (median) cumulative duration of follow-up. The rates of multiple outcome pairs were significantly influenced by hormone therapy, especially over cumulative follow-up, providing potential clinical and mechanistic insights. For example, among women randomized to either regimen, hazard ratios for pairs defined by fracture during intervention followed by death from any cause were reduced and hazard ratios for pairs defined by gallbladder disease followed by death were increased, though these findings may primarily reflect single-outcome associations. In comparison, hazard ratios for diabetes followed by death were reduced with CEE but not with CEE + MPA, and those for hypertension followed by death were increased with CEE + MPA but not with CEE.

Effects of oral conjugated equine estrogens with or without medroxyprogesterone acetate on incident hypertension in the Women's Health Initiative hormone therapy trials

OBJECTIVE

The aim of the study was to determine the effect of menopausal hormone therapy on incident hypertension in the two Women's Health Initiative hormone therapy trials and in extended postintervention follow-up.

METHODS

A total of 27,347 postmenopausal women aged 50 to 79 years were enrolled at 40 US centers. This analysis includes the subsample of 18,015 women who did not report hypertension at baseline and were not taking antihypertensive medication. Women with an intact uterus received conjugated equine estrogens (CEE; 0.625 mg/d) plus medroxyprogesterone acetate (MPA; 2.5 mg/d) (n = 5,994) or placebo (n = 5,679). Women with prior hysterectomy received CEE alone (0.625 mg/d) (n = 3,108) or placebo (n = 3,234). The intervention lasted a median of 5.6 years in the CEE plus MPA trial and 7.2 years in the CEE-alone trial with 13 years of cumulative follow-up until September 30, 2010. The primary outcome for these analyses was self-report of a new diagnosis of hypertension and/or high blood pressure requiring treatment with medication.

RESULTS

During the CEE and CEE plus MPA intervention phase, the rate of incident hypertension was 18% higher for intervention than for placebo (CEE: hazard ratio [HR], 1.18; 95% CI, 1.09-1.29; CEE plus MPA: HR, 1.18; 95% CI, 1.09-1.27). This effect dissipated postintervention in both trials (CEE: HR, 1.06; 95% CI, 0.94-1.20; CEE plus MPA: HR, 1.02; 95% CI, 0.94-1.10).

CONCLUSIONS

CEE (0.625 mg/d) administered orally, with or without MPA, is associated with an increased risk of hypertension in older postmenopausal women. Whether lower doses, different estrogen formulations, or transdermal route of administration offer lower risks warrant further study.

Serum metabolomic profiles associated with postmenopausal hormone use

INTRODUCTION

Postmenopausal hormone use is linked to several health outcomes and the risk associated with some may differ depending on whether estrogen is used alone or in combination with progestin.

OBJECTIVE

Metabolomic analyses of postmenopausal hormone use and differences between hormone regimes was done to identify metabolites associated with each type of hormone treatment.

METHODS

Untargeted metabolomics analysis was done on serum from 1336 women enrolled in the Cancer Prevention II Nutrition Cohort. Levels of 781 named metabolites were compared between 667 nonusers with 332 estrogen-only and with 337 estrogen plus progestin users using linear regression. Metabolite levels were also compared between estrogen-only and estrogen plus progestin users.

RESULTS

Compared to nonusers, 276 metabolites were statistically significantly (P < 6.40 × 10^- 5) associated with estrogen-only use and 222 were associated with estrogen plus progestin use. The metabolites associated with both types of hormones included numerous lipids, acyl carnitines, and amino acids as well as the thyroid hormone thyroxine and the oncometabolite fumarate. The 65 metabolites that differed significantly between estrogen-only and estrogen plus progestin users included 19 steroids and 12 lipids that contained the bioactive fatty acid arachidonic acid.

CONCLUSIONS

These findings suggest that postmenopausal hormone use influences metabolic pathways linked to a variety of cellular processes, including the regulation of metabolism and stress responses, energy production, and inflammation. The differential association of numerous lipids which influence cellular signaling suggests that differences in signal transduction may contribute to the disparate risks for some diseases between estrogen-only and estrogen plus progestin users.

Assessing biological and technological variability in protein levels measured in pre-diagnostic plasma samples of women with breast cancer

Background

Quantitative proteomics allows for the discovery and functional investigation of blood-based pre-diagnostic biomarkers for early cancer detection. However, a major limitation of proteomic investigations in biomarker studies remains the biological and technical variability in the analysis of complex clinical samples. Moreover, unlike ‘omics analogues such as genomics and transcriptomics, proteomics has yet to achieve reproducibility and long-term stability on a unified technological platform. Few studies have thoroughly investigated protein variability in pre-diagnostic samples of cancer patients across multiple platforms.

Methods

We obtained ten blood plasma “case” samples collected up to 2 years prior to breast cancer diagnosis. Each case sample was paired with a matched control plasma from a full biological sister without breast cancer. We measured protein levels using both mass-spectrometry and antibody-based technologies to: (1) assess the technical considerations in different protein assays when analyzing limited clinical samples, and (2) evaluate the statistical power of potential diagnostic analytes.

Results

Although we found inherent technical variation in the three assays used, we detected protein dependent biological signal from the limited samples. The three assay types yielded 32 proteins with statistically significantly (p < 1E-01) altered expression levels between cases and controls, with no proteins retaining statistical significance after false discovery correction.

Conclusions

Technical, practical, and study design considerations are essential to maximize information obtained in limited pre-diagnostic samples of cancer patients. This study provides a framework that estimates biological effect sizes critical for consideration in designing studies for pre-diagnostic blood-based biomarker detection.

Electronic supplementary material

The online version of this article (10.1186/s40364-017-0110-y) contains supplementary material, which is available to authorized users.

Augmented case-only designs for randomized clinical trials with failure time endpoints

Under suitable assumptions and by exploiting the independence between inherited genetic susceptibility and treatment assignment, the case-only design yields efficient estimates for subgroup treatment effects and gene-treatment interaction in a Cox model. However it cannot provide estimates of the genetic main effect and baseline hazards, that are necessary to compute the absolute disease risk. For two-arm, placebo-controlled trials with rare failure time endpoints, we consider augmenting the case-only design with random samples of controls from both arms, as in the classical case-cohort sampling scheme, or with a random sample of controls from the active treatment arm only. The latter design is motivated by vaccine trials for cost-effective use of resources and specimens so that host genetics and vaccine-induced immune responses can be studied simultaneously in a bigger set of participants. We show that these designs can identify all parameters in a Cox model and that the efficient case-only estimator can be incorporated in a two-step plug-in procedure. Results in simulations and a data example suggest that incorporating case-only estimators in the classical case-cohort design improves the precision of all estimated parameters; sampling controls only in the active treatment arm attains a similar level of efficiency.

Plasma matrix metalloproteinase 2 levels and breast cancer risk

Matrix metalloproteinase 2 (MMP2) is an enzyme with important functions in breast cancer invasion and metastasis. However, it is unclear whether circulating MMP2 levels may predict breast cancer risk. We conducted a prospective nested case-control analysis in the Nurses' Health Study among 1136 cases who were diagnosed with invasive breast cancer between 1992 and 2004 and 1136 matched controls. All participants provided blood samples in 1989-1990, and a subset (170 cases, 170 controls) contributed an additional sample in 2000-2002. Pre-diagnostic plasma MMP2 levels were measured via immunoassay, and conditional logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs), adjusted for breast cancer risk factors. No association was observed between plasma MMP2 levels and risk of total invasive breast cancer (top vs. bottom quartile, OR=1.0; 95% CI: 0.7, 1.2; p-trend=0.89). Findings did not vary significantly by time since blood draw, body mass index, postmenopausal hormone use, or menopausal status at either blood draw or breast cancer diagnosis. MMP2 was associated with a greater risk of nodal metastases at diagnosis (top vs. bottom quartile, OR=1.5; 95% CI: 1.0, 2.2; p-heterogeneity, any vs. no lymph nodes=0.002), but no significant associations were observed with other tumor characteristics or with recurrent or fatal cancers. Plasma MMP2 levels do not appear to be predictive of total invasive breast cancer risk, although associations with aggressive disease warrant further study.

Positive association between 25-hydroxyvitamin D and C-reactive protein is confounded by hormonal contraceptive use

BACKGROUND

Studies of the relationship between vitamin D and inflammation are equivocal. This may be due to unaccounted confounding. Hormonal contraceptive (HC) use is associated with elevated circulating 25-hydroxyvitamin D [25(OH)D] in Caucasians and African-Americans, but its effects on 25(OH)D in other ethnicities are unclear. HC use is associated with elevated C-reactive protein (CRP), an inflammatory biomarker. Our objectives were to assess the effect of HC use on 25(OH)D across ethnic groups, and to examine the association between HC, 25(OH)D and CRP in an ethnically diverse population of young adults.

METHODS

We recruited Caucasian, East Asian, and South Asian individuals (n=1,403) from Toronto, Canada. Fasting blood measures of 25(OH)D and CRP were obtained.

RESULTS

Across ethnic groups, women HC users (n=280) had higher 25(OH)D and CRP than women HC non-users (n=695) and men (n=428) (p<0.008 and p<0.0001, respectively). Circulating 25(OH)D was positively associated with CRP in the entire population in models not accounting for HC use (β=0.010±0.003; p<0.0001). There was no association when men and women HC non-users were examined separately. Among women HC users, there was no association after accounting for hormone dose. A positive association between 25(OH)D and CRP among individuals above the median 25(OH)D (≥51.9 nmol/L) was not significant after adjustment for HC use. No association was observed among individuals below the median.

CONCLUSIONS

HC use and 25(OH)D were positively associated across ethnic groups. We found no association between 25(OH)D and CRP when HC use was accounted for. HC use confounds the association between 25(OH)D and CRP.

Postmenopausal hormone therapy and the risks of coronary heart disease, breast cancer, and stroke

The principal findings are briefly reviewed from the Women's Health Initiative trials of the most commonly used postmenopausal hormone regimens in the United States-conjugated equine estrogens and these same estrogens plus medroxyprogesterone acetate. A more detailed review is presented for three major clinical outcomes: coronary heart disease (CHD), the primary trial outcome for which a major benefit was hypothesized; invasive breast cancer, the primary safety outcome for which some adverse effect was expected; and stroke which surfaced as an important adverse effect with both regimens, and one that is influential in decisions concerning the continued use of postmenopausal estrogens alone. The review for these outcomes includes an update on interactions of treatment effects with study subject characteristics and exposures and with prerandomization biomarker levels. It also includes a focus on timing issues that are important to the understanding of treatment effects. Specifically, with combined estrogen plus progestin, CHD risk was elevated early with the elevation dissipating after a few years of treatment, whereas breast cancer elevations increased during the treatment period, and climbed to about a threefold increase following 5 years of adherence. Importantly, breast cancer risk elevations appear to be higher among women who initiate treatment at the menopause, or soon thereafter, compared with women having a longer gap time. Stroke effects, on the contrary, did not seem to vary appreciably with these timing issues. The adverse effect was evidently localized to ischemic strokes, for which there was an approximate 50% increase with either regimen. The rather limited knowledge concerning the biomarkers and biological pathways that mediate the hormone therapy effects on these diseases is also briefly reviewed.

Hormone replacement therapy and venous thromboembolism

Hormone replacement therapy (HRT) for post-menopausal women is known to promote venous thromboembolism (VTE), i.e., deep venous thrombosis and pulmonary embolism, though the absolute risk for a given patient is very small. The risk of VTE appears to be greatest soon after the initiation of HRT and returns to the baseline level of risk of non-HRT users after discontinuation. There is inconsistent data about whether estrogen-only or combined estrogen-progestin HRT are associated with similar VTE risk. Retrospective analyses suggest that transdermal HRT is not as prothrombotic as oral HRT, though this has not been evaluated in randomized clinical trials. Increasing age and weight further promote HRT's VTE risk. Some studies have investigated whether prothrombotic combinations may increase HRT's VTE risk and there is evidence that Factor V Leiden may do this. However, no benefit to screening prospective HRT users has been described, yet. Advanced proteomic and genomic studies may hold promise in the future for better elucidating which HRT users are at highest risk for VTE. Presently, physicians and prospective HRT users should discuss the potential risks and benefits for the individual patient, acknowledging there is no way to fully mitigate the risk of VTE. This article is part of a Special Issue entitled 'Menopause'.

Proteomic risk markers for coronary heart disease and stroke: validation and mediation of randomized trial hormone therapy effects on these diseases

BACKGROUND

We previously reported mass spectrometry-based proteomic discovery research to identify novel plasma proteins related to the risk of coronary heart disease (CHD) and stroke, and to identify proteins with concentrations affected by the use of postmenopausal hormone therapy. Here we report CHD and stroke risk validation studies for highly ranked proteins, and consider the extent to which protein concentration changes relate to disease risk or provide an explanation for hormone therapy effects on these outcomes.

METHODS

Five proteins potentially associated with CHD (beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), thrombospondin-1(THBS1), complement factor D pre-protein (CFD), and insulin-like growth factor binding protein 1 (IGFBP1)) and five potentially associated with stroke (B2M, IGFBP2, IGFBP4, IGFBP6, and hemopexin (HPX)) had high discovery phase significance level ranking and an available ELISA assay, and were included in case-control validation studies within the Women's Health Initiative (WHI) hormone therapy trials. Protein concentrations, at baseline and 1 year following randomization, were assessed for 358 CHD cases and 362 stroke cases, along with corresponding disease-free controls. Disease association, and mediation of estrogen-alone and estrogen plus progestin effects on CHD and stroke risk, were assessed using logistic regression.

RESULTS

B2M, THBS1, and CFD were confirmed (P <0.05) as novel CHD risk markers, and B2M, IGFBP2, and IGFBP4 were confirmed as novel stroke disease risk markers, while the assay for HPX proved to be unreliable. The change from baseline to 1 year in B2M was associated (P <0.05) with subsequent stroke risk, and trended similarly with subsequent CHD risk. Change from baseline to 1 year in IGFBP1 was also associated with CHD risk, and this change provided evidence of hormone therapy effect mediation.

CONCLUSIONS

Plasma B2M is confirmed to be an informative risk marker for both CHD and stroke. The B2M increase experienced by women during the first year of hormone therapy trial participation conveys cardiovascular disease risk. The increase in IGFBP1 similarly conveys CHD risk, and the magnitude of the IGFBP1 increase following hormone therapy may be a mediator of hormone therapy effects. Plasma THBS1 and CFD are confirmed as CHD risk markers, and plasma IGFBP4 and IGFBP2 are confirmed as stroke risk markers.

CLINICAL TRIALS REGISTRATION

ClinicalTrials.gov identifier: NCT00000611.

Proteomic analysis of venous thromboembolism: an update

Venous thromboembolism is a complex, multifactorial disorder, the pathogenesis of which typically involves a variety of inherited or acquired factors. The multifactorial etiology of this disease and the partial correlation between genotype and prothrombotic phenotype limit greatly the value of genetic analysis in assessing thrombotic risk. The integration of several new 'omics' techniques enables a multifaceted and holistic approach to the study of venous thrombotic processes and pave the way to the search and identification of novel blood biomarkers and/or effectors of thrombus formation that can also be the possible future target of new anticoagulant and thrombolytic therapies for more personalized medicine. This review provides a comprehensive overview of the latest candidate proteomic biomarkers of venous thrombosis and of the proteomics studies relevant to its pathophysiology, some of which seem to confirm the existence of a common physiopathological basis for venous thromboembolism and atherothrombosis.

Proteomic profiling of the autoimmune response to breast cancer antigens uncovers a suppressive effect of hormone therapy

PURPOSE

Proteomics technologies are well suited for harnessing the immune response to tumor antigens for diagnostic applications as in the case of breast cancer. We previously reported a substantial impact of hormone therapy (HT) on the proteome. Here, we investigated the effect of HT on the immune response toward breast tumor antigens.

EXPERIMENTAL DESIGN

Plasmas collected 0-10 months prior to diagnosis of ER+ breast cancer from 190 postmenopausal women and 190 controls that participated in the Women's Health Initiative Observational Study were analyzed for the effect of HT on IgG reactivity against arrayed proteins from MCF-7 or SKBR3 breast cancer cell line lysates following extensive fractionation.

RESULTS

HT user cases exhibited significantly reduced autoantibody reactivity against arrayed proteins compared to cases who were Not Current users. An associated reduced level of IL-6 and other immune-related cytokines was observed among HT users relative to nonusers.

CONCLUSION AND CLINICAL RELEVANCE

Our findings suggest occurrence of a global altered immune response to breast cancer-derived proteins associated with HT. Thus a full understanding of factors that modulate the immune response is necessary to translate autoantibody panels into clinical applications.

A call for a fresh new look at the plasma proteome

Serum and plasma from which serum is derived represent a substantial challenge for proteomics due to their complexity. A landmark plasma proteome study was initiated a decade ago by the Human Proteome Organization (HUPO) that had as an objective to examine the capabilities of existing technologies. Given the advances in proteomics and the continued interest in the plasma proteome, it would timely reassess the depth and breadth of analysis of plasma that can be achieved with current methodology and instrumentation. A collaborative project to define the plasma proteome and its variation, with a plan to build a plasma proteome database would be timely.

Novel effects of hormonal contraceptive use on the plasma proteome

Background

Hormonal contraceptive (HC) use may increase cardiometabolic risk; however, the effect of HC on emerging cardiometabolic and other disease risk factors is not clear.

Objectives

To determine the association between HC use and plasma proteins involved in established and emerging disease risk pathways.

Method

Concentrations of 54 high-abundance plasma proteins were measured simultaneously by LC-MRM/MS in 783 women from the Toronto Nutrigenomics and Health Study. C-reactive protein (CRP) was measured separately. ANCOVA was used to test differences in protein concentrations between users and non-users, and among HC users depending on total hormone dose. Linear regression was used to test the association between duration (years) of HC use and plasma protein concentrations. Principal components analysis (PCA) was used to identify plasma proteomic profiles in users and non-users.

Results

After Bonferroni correction, 19 proteins involved in inflammation, innate immunity, coagulation and blood pressure regulation were significantly different between users and non-users (P<0.0009). These differences were replicated across three distinct ethnocultural groups. Traditional markers of glucose and lipid metabolism were also significantly higher among HC users. Neither hormone dose nor duration of use affected protein concentrations. PCA identified 4 distinct proteomic profiles in users and 3 in non-users.

Conclusion

HC use was associated with different concentrations of plasma proteins along various disease-related pathways, and these differences were present across different ethnicities. Aside from the known effect of HC on traditional biomarkers of cardiometabolic risk, HC use also affects numerous proteins that may be biomarkers of dysregulation in inflammation, coagulation and blood pressure.

Exploring the interaction between SNP genotype and postmenopausal hormone therapy effects on stroke risk

BACKGROUND

Genome-wide association studies have identified several genomic regions that are associated with stroke risk, but these provide an explanation for only a small fraction of familial stroke aggregation. Genotype by environment interactions may contribute further to such an explanation. The Women's Health Initiative (WHI) clinical trial found increased stroke risk with postmenopausal hormone therapy (HT) and provides an efficient setting for evaluating genotype-HT interaction on stroke risk.

METHODS

We examined HT by genotype interactions for 392 SNPs selected from candidate gene studies, and 2,371 SNPs associated with changes in blood protein concentrations after hormone therapy, in analyses that included 2,045 postmenopausal women who developed stroke during WHI clinical trial and observational study follow-up and one-to-one matched controls. A two-stage procedure was implemented where SNPs passing the first stage screening based on marginal association with stroke risk were tested in the second stage for interaction with HT using case-only analysis.

RESULTS

The two-stage procedure identified two SNPs, rs2154299 and rs12194855, in the coagulation factor XIII subunit A (F13A1) region and two SNPs, rs630431 and rs560892, in the proprotein convertase subtilisin kexin 9 (PCSK9) region, with an estimated false discovery rate <0.05 based on interaction tests. Further analyses showed significant stroke risk interaction between these F13A1 SNPs and estrogen plus progestin (E+P) treatment for ischemic stroke and for ischemic and hemorrhagic stroke combined, and suggested interactions between PCSK9 SNPs with either E+P or estrogen-alone treatment.

CONCLUSIONS

Genotype by environment interaction information may help to define genomic regions relevant to stroke risk. Two-stage analysis among postmenopausal women generates novel hypotheses concerning the F13A1 and PCSK9 genomic regions and the effects of hormonal exposures on postmenopausal stroke risk for subsequent independent validation.

Conjugated equine oestrogen and breast cancer incidence and mortality in postmenopausal women with hysterectomy: extended follow-up of the Women's Health Initiative randomised placebo-controlled trial

BACKGROUND

By contrast with many observational studies, women in the Women's Health Initiative (WHI) trial who were randomly allocated to receive oestrogen alone had a lower incidence of invasive breast cancer than did those who received placebo. We aimed to assess the influence of oestrogen use on longer term breast cancer incidence and mortality in extended follow-up of this cohort.

METHODS

Between 1993 and 1998, the WHI enrolled 10,739 postmenopausal women from 40 US clinical centres into a randomised, double-masked, placebo-controlled trial. Women aged 50-79 years who had undergone hysterectomy and had expected 3-year survival and mammography clearance were randomly allocated by a computerised, permuted block algorithm, stratified by age group and centre, to receive oral conjugated equine oestrogen (0·625 mg per day; n=5310) or matched placebo (n=5429). The trial intervention was terminated early on Feb 29, 2004, because of an adverse effect on stroke. Follow-up continued until planned termination (March 31, 2005). Consent was sought for extended surveillance from the 9786 living participants in active follow-up, of whom 7645 agreed. Using data from this extended follow-up (to Aug 14, 2009), we assessed long-term effects of oestrogen use on invasive breast cancer incidence, tumour characteristics, and mortality. We used Cox regression models to estimate hazard ratios (HRs) in the intention-to-treat population. This study is registered with ClinicalTrials.gov, number NCT00000611.

FINDINGS

After a median follow-up of 11·8 years (IQR 9·1-12·9), the use of oestrogen for a median of 5·9 years (2·5-7·3) was associated with lower incidence of invasive breast cancer (151 cases, 0·27% per year) compared with placebo (199 cases, 0·35% per year; HR 0·77, 95% CI 0·62-0·95; p=0·02) with no difference (p=0·76) between intervention phase (0·79, 0·61-1·02) and post-intervention phase effects (0·75, 0·51-1·09). In subgroup analyses, we noted breast cancer risk reduction with oestrogen use was concentrated in women without benign breast disease (p=0·01) or a family history of breast cancer (p=0·02). In the oestrogen group, fewer women died from breast cancer (six deaths, 0·009% per year) compared with controls (16 deaths, 0·024% per year; HR 0·37, 95% CI 0·13-0·91; p=0·03). Fewer women in the oestrogen group died from any cause after a breast cancer diagnosis (30 deaths, 0·046% per year) than did controls (50 deaths, 0·076%; HR 0·62, 95% CI 0·39-0·97; p=0·04).

INTERPRETATION

Our findings provide reassurance for women with hysterectomy seeking relief of climacteric symptoms in terms of the effects of oestrogen use for about 5 years on breast cancer incidence and mortality. However, our data do not support use of oestrogen for breast cancer risk reduction because any noted benefit probably does not apply to populations at increased risk of such cancer.

FUNDING

US National Heart, Lung, and Blood Institute; Wyeth.

Concordant release of glycolysis proteins into the plasma preceding a diagnosis of ER+ breast cancer

Although the identification of peripheral blood biomarkers would enhance early detection strategies for breast cancer, the discovery of protein markers has been challenging. In this study, we sought to identify coordinated changes in plasma proteins associated with breast cancer based on large-scale quantitative mass spectrometry. We analyzed plasma samples collected up to 74 weeks before diagnosis from 420 estrogen receptor (ER)(+) cases and matched controls enrolled in the Women's Health Initiative cohort. A gene set enrichment analysis was applied to 467 quantified proteins, linking their corresponding genes to particular biologic pathways. On the basis of differences in the concentration of individual proteins, glycolysis pathway proteins exhibited a statistically significant difference between cases and controls. In particular, the enrichment was observed among cases in which blood was drawn closer to diagnosis (effect size for the 0-38 weeks prediagnostic group, 1.91; P, 8.3E-05). Analysis of plasmas collected at the time of diagnosis from an independent set of cases and controls confirmed upregulated levels of glycolysis proteins among cases relative to controls. Together, our findings indicate that the concomitant release of glycolysis proteins into the plasma is a pathophysiologic event that precedes a diagnosis of ER(+) breast cancer.

A regularized Hotelling's T2 test for pathway analysis in proteomic studies

Recent proteomic studies have identified proteins related to specific phenotypes. In addition to marginal association analysis for individual proteins, analyzing pathways (functionally related sets of proteins) may yield additional valuable insights. Identifying pathways that differ between phenotypes can be conceptualized as a multivariate hypothesis testing problem: whether the mean vector μ of a p-dimensional random vector X is μ₀ . Proteins within the same biological pathway may correlate with one another in a complicated way, and type I error rates can be inflated if such correlations are incorrectly assumed to be absent. The inflation tends to be more pronounced when the sample size is very small or there is a large amount of missingness in the data, as is frequently the case in proteomic discovery studies. To tackle these challenges, we propose a regularized Hotelling's T² (RHT) statistic together with a non-parametric testing procedure, which effectively controls the type I error rate and maintains good power in the presence of complex correlation structures and missing data patterns. We investigate asymptotic properties of the RHT statistic under pertinent assumptions and compare the test performance with four existing methods through simulation examples. We apply the RHT test to a hormone therapy proteomics data set, and identify several interesting biological pathways for which blood serum concentrations changed following hormone therapy initiation.

Estrogen in cycling rats alters gene expression in the temporomandibular joint, trigeminal ganglia and trigeminal subnucleus caudalis/upper cervical cord junction

Females report temporomandibular joint (TMJ) pain more than men and studies suggest estrogen modulates this pain response. Our goal in this study was to determine genes that are modulated by physiological levels of 17β-estradiol that could have a role in TMJ pain. To complete this goal, saline or complete Freund's adjuvant was injected in the TMJ when plasma 17β-estradiol was low or when it was at a high proestrus level. TMJ, trigeminal ganglion, and trigeminal subnucleus caudalis/upper cervical cord junction (Vc/C(1-2) ) tissues were isolated from the treated rats and expression of 184 genes was quantitated in each tissue using real-time PCR. Significant changes in the amount of specific transcripts were observed in the TMJ tissues, trigeminal ganglia, and Vc/C(1-2) region when comparing rats with high and low estrogen. GABA A receptor subunit α6 (Gabra6) and the glycine receptor α2 (Glra2) were two genes of interest because of their direct function in neuronal activity and a >29-fold increase in the trigeminal ganglia was observed in proestrus rats with TMJ inflammation. Immunohistochemical studies showed that Gabrα6 and Glrα2 neuronal and not glial expression increased when comparing rats with high and low estrogen. Estrogen receptors α and β are present in neurons of the trigeminal ganglia, whereby 17β-estradiol can alter expression of Gabrα6 and Glrα2. Also, estrogen receptor α (ERα) but not ERβ was observed in satellite glial cells of the trigeminal ganglia. These results demonstrate that genes associated with neurogenic inflammation or neuronal excitability were altered by changes in the concentration of 17β-estradiol.

Progress in mining the human proteome for disease applications

Currently available technologies allow in-depth analysis of multiple facets of the proteome that have clinical relevance and that complement current genomics-based approaches. Although some progress has been made in our knowledge of the human proteome in health and in disease, there is an urgent need to chart a coherent road map with clearly defined milestones to guide proteomics efforts. Areas of emphasis include: (1) building resources, (2) filling gaps in our understanding of biological variation, and (3) systematically characterizing proteome alterations that occur in well-defined disease states, all of which require an organized and collaborative effort.

Searching for the noninvasive biomarker holy grail: are urine proteomics the answer?

Recently, biobehavioral nursing scientists have focused their attention on the search for biomarkers or biological signatures to identify patients at risk for various health problems and poor disease outcomes. In response to the national impetus for biomarker discovery, the measurement of biological fluids and tissues has become increasingly sophisticated. Urine proteomics, in particular, may hold great promise for biobehavioral focused nursing scientists for examination of symptom-and syndrome-related research questions. Urine proteins are easily accessible secreted proteins that provide direct and indirect windows into bodily functions. Advances in proteomics and biomarker discovery provide new opportunities to conduct research studies with banked and fresh urine to benefit diagnosis, prognosis, and evaluation of outcomes in various disease populations. This article provides a review of proteomics and a rationale for utilizing urine proteomics in biobehavioral research. It addresses as well some of the challenges involved in data collection and sample preparation.

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.

Confounding effects of hormone replacement therapy in protein biomarker studies

BACKGROUND

We have recently investigated effects of hormone replacement therapy (HRT) on the serum proteome, and found a high proportion of proteins with altered levels associated with oral estrogen and/or estrogen plus progesterone treatment. Given this finding, we have investigated the extent to which exposure to HRT may have a confounding effect in the assessment of circulating proteins as cancer biomarkers.

METHODS

We utilize mass spectrometry data collected from the HRT serum proteome studies to estimate the overall effect of postmenopausal hormone therapy on candidate ovarian cancer biomarkers that have been previously reported.

RESULTS

Levels of approximately half of the proteins reported as potential ovarian cancer biomarkers were found to be affected by HRT. The impact of HRT on levels of insulin-like growth factor and inhibin protein families was found to be substantial.

CONCLUSIONS

We conclude that the potential confounding effect of HRT and other types of exposures should be taken into consideration in cancer biomarker study design.

IMPACT

HRT significantly affects the serum proteome and should be taken into account as part of biomarker study design and data analysis.

Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

Background

Coronary heart disease (CHD) and stroke were key outcomes in the Women's Health Initiative (WHI) randomized trials of postmenopausal estrogen and estrogen plus progestin therapy. We recently reported a large number of changes in blood protein concentrations in the first year following randomization in these trials using an in-depth quantitative proteomics approach. However, even though many affected proteins are in pathways relevant to the observed clinical effects, the relationships of these proteins to CHD and stroke risk among postmenopausal women remains substantially unknown.

Methods

The same in-depth proteomics platform was applied to plasma samples, obtained at enrollment in the WHI Observational Study, from 800 women who developed CHD and 800 women who developed stroke during cohort follow-up, and from 1-1 matched controls. A plasma pooling strategy, followed by extensive fractionation prior to mass spectrometry, was used to identify proteins related to disease incidence, and the overlap of these proteins with those affected by hormone therapy was examined. Replication studies, using enzyme-linked-immunosorbent assay (ELISA), were carried out in the WHI hormone therapy trial cohorts.

Results

Case versus control concentration differences were suggested for 37 proteins (nominal P < 0.05) for CHD, with three proteins, beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), and insulin-like growth factor binding protein acid labile subunit (IGFALS) having a false discovery rate < 0.05. Corresponding numbers for stroke were 47 proteins with nominal P < 0.05, three of which, apolipoprotein A-II precursor (APOA2), peptidyl-prolyl isomerase A (PPIA), and insulin-like growth factor binding protein 4 (IGFBP4), have a false discovery rate < 0.05. Other proteins involved in insulin-like growth factor signaling were also highly ranked. The associations of B2M with CHD (P < 0.001) and IGFBP4 with stroke (P = 0.005) were confirmed using ELISA in replication studies, and changes in these proteins following the initiation of hormone therapy use were shown to have potential to help explain hormone therapy effects on those diseases.

Conclusions

In-depth proteomic discovery analysis of prediagnostic plasma samples identified B2M and IGFBP4 as risk markers for CHD and stroke respectively, and provided a number of candidate markers of disease risk and candidate mediators of hormone therapy effects on CHD and stroke.

Clinical Trials Registration

ClinicalTrials.gov identifier: NCT00000611

Integrative proteomic analysis of serum and peritoneal fluids helps identify proteins that are up-regulated in serum of women with ovarian cancer

BACKGROUND

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments.

METHODOLOGY

Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays.

FINDINGS

We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here.

CONCLUSION

Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.