A two-gene expression ratio of homeobox 13 and interleukin-17B receptor for prediction of recurrence and survival in women receiving adjuvant tamoxifen

Selecting postoperative adjuvant systemic therapy for early-stage breast cancer: An updated assessment and systematic review of leading commercially available gene expression assays

Gene expression assays (GEAs) can guide treatment for early-stage breast cancer. Several large prospective randomized clinical trials, and numerous additional studies, now provide new information for selecting an appropriate GEA. This systematic review builds upon prior reviews, with a focus on five widely commercialized GEAs (Breast Cancer Index®, EndoPredict®, MammaPrint®, Oncotype DX®, and Prosigna®). The comprehensive dataset available provides a contemporary opportunity to assess each GEA's utility as a prognosticator and/or predictor of adjuvant therapy benefit.

Gene Expression Assays to Tailor Adjuvant Endocrine Therapy for HR+/HER2- Breast Cancer

Adjuvant endocrine therapy (ET) represents the standard of care for almost all hormone receptor (HR)+/HER2- breast cancers, and different agents and durations are currently available. In this context, the tailoring and optimization of adjuvant endocrine treatment by reducing unnecessary toxic treatment while taking into account the biological heterogeneity of HR+/HER2- breast cancer represents a clinical priority. There is therefore a significant need for the integration of biological biomarkers in the choice of adjuvant ET beyond currently used clinicopathological characteristics. Several gene expression assays have been developed to identify patients with HR+/HER2- breast cancer who will not derive benefit from the addition of adjuvant chemotherapy. By enhancing risk stratification and predicting therapeutic response, genomic assays have also shown to be a promising tool for optimizing endocrine treatment decisions. In this study, we review evidence supporting the use of most common commercially available gene expression assays [Oncotype DX, MammaPrint, Breast Cancer Index (BCI), Prosigna, and EndoPredict] in tailoring adjuvant ET. Available data on the use of genomic tests to inform extended adjuvant treatment choice based on the risk of late relapse and on the estimated benefit of a prolonged ET are discussed. Moreover, preliminary evidence regarding the use of genomic assays to inform de-escalation of endocrine treatment, such as shorter durations or omission, for low-risk patients is reviewed. Overall, gene expression assays are emerging as potential tools to further personalize adjuvant treatment for patients with HR+/HER2- breast cancers.

Gene expression signatures in older patients with breast cancer: A systematic review

BACKGROUND

Gene expression signatures have emerged to predict prognosis and guide the use of adjuvant therapy in patients with hormone receptor-positive breast cancer. The objective of this systematic review was to evaluate the prognostic and predictive value of commercially available gene expression signatures as a tool in adjuvant treatment decision-making in older patients with breast cancer.

METHODS

PubMed, MEDLINE, Embase, Web of Science, Cochrane Library, and Emcare were reviewed for relevant articles published before December 2021. Eligible studies were randomised trials and cohort studies that externally validated commercially available gene expression signatures in patients aged 65 years and older, including studies that presented subanalyses of this age group. Data extraction and risk of bias assessment was performed independently by two investigators.

RESULTS

Fifteen studies were included. Most studies investigated Oncotype DX, while results from other gene expression signatures were limited. Several studies underlined the prognostic performance of Oncotype DX and Prosigna Risk of Recurrence in older patients. Moreover, Oncotype DX was predictive for older patients with an intermediate-risk recurrence score; chemotherapy could be spared in both lymph node-positive and lymph node-negative disease.

CONCLUSIONS

Prognostic performance has been demonstrated in older patients for several gene expression signatures. However, additional validation in patients with high-risk tumours is needed before gene expression signatures can be implemented in clinical practice as a prediction tool for adjuvant chemotherapy decision-making in the older age group.

Tailoring neoadjuvant treatment of HR-positive/HER2-negative breast cancers: Which role for gene expression assays?

Neoadjuvant chemotherapy (NACT) for breast cancer (BC) increases surgical and conservative surgery chances. However, a significant proportion of patients will not be eligible for conservative surgery following NACT because of large tumor size and/or low chemosensitivity, especially for hormone receptor (HR)-positive/ human epidermal growth factor receptor 2 (HER2)-negative tumors, for which pathological complete response rates are lower than for other BC subtypes. On the other hand, for luminal BC neoadjuvant endocrine therapy could represent a valid alternative. Several gene expression assays have been introduced into clinical practice in last decades, in order to define prognosis more accurately than clinico-pathological features alone and to predict the benefit of adjuvant treatments. A series of studies have demonstrated the feasibility of using core needle biopsy for gene expression risk testing, finding a high concordance rate in the risk result between biopsy sample and surgical samples. Based on these premises, recent efforts have focused on the utility of gene expression signatures to guide therapeutic decisions even in the neoadjuvant setting. Several prospective and retrospective studies have investigated the correlation between gene expression risk score from core needle biopsy before neoadjuvant therapy and the likelihood of 1) clinical and pathological response to neoadjuvant chemotherapy and endocrine therapy, 2) conservative surgery after neoadjuvant chemotherapy and endocrine therapy, and 3) survival following neoadjuvant chemotherapy and endocrine therapy. The purpose of this review is to provide an overview of the potential clinical utility of the main commercially available gene expression panels (Oncotype DX, MammaPrint, EndoPredict, Prosigna/PAM50 and Breast Cancer Index) in the neoadjuvant setting, in order to better inform decision making for luminal BC beyond the exclusive contribution of clinico-pathological features.

The significance of HOXB7 and IL17RB serum levels in prognosis of hormonally dependent breast cancer: A pilot study

PURPOSE

Improved prognostication of a patient's outcome could allow for personalized treatment decisions in breast cancer. Homeobox B7 (HOXB7) and interleukin 17 receptor B (IL17RB) are proteins reportedly involved in the development of hormonal therapy resistance. Their prognostic value was previously investigated in tumor tissue but recent mass spectrometric detection of HOXB7 and IL17RB proteins in serum has prompted us to perform the first prognostic evaluation of their serum levels.

PATIENTS AND METHODS

The study included 81 premenopausal breast cancer patients that received adjuvant hormonal therapy. The median follow-up period was 61 months. HOXB7 and IL17RB serum protein levels were measured by quantitative sandwich ELISA and prognostically evaluated by Cox proportional hazards regression analysis.

RESULTS

HOXB7 protein was detected in 96.3% and IL17RB in 33.3% of serum samples. Higher levels of serum HOXB7 significantly associated with favorable disease outcome by prognosticating distant (by HR ​= ​0.04; P ​= ​0.001) and local recurrence (by HR ​= ​0.03, P ​= ​0.001). The recurrence rates in the HOXB7^high and HOXB7^low subgroups of patients (cut-off 81.5 ​pg/mL) were 0% and 17%, respectively. Serum IL17RB levels did not significantly associate with either local or distant events. The multivariate analysis highlighted estrogen receptor, histological grade, nodal status and HOXB7 as independent prognostic parameters.

CONCLUSIONS

Our findings validate the previous mass-spectrometry data by showing that HOXB7 and IL17RB cellular proteins are detectable in serum by a standard ELISA assay. Furthermore, we show that HOXB7 serum levels are the relevant prognosticator of response to hormonal therapy.

Gene Expression Assay in the Management of Early Breast Cancer

The addition of adjuvant chemotherapy to hormonal therapy is often considered questionable in patients with estrogen receptor-positive early breast cancer. Low risk of disease relapse after endocrine treatment alone and/or a low sensitivity to chemotherapy are reasons behind not all patients benefit from chemotherapy. Most of the patients could be exposed to unnecessary treatment- related adverse events and health care costs when treatment decision-making is based only on classical clinical histological features. Gene expression profile has been developed to refine physician's decision-making process and to tailor personalized treatment to patients. In particular, these tests are designed to spare patients the side effects of unnecessary treatment, and ensure that adjuvant chemotherapy is correctly recommended to patients with early breast cancer. In this review, we will discuss the main diagnostic tests and their potential clinical applications (Oncotype DX, MammaPrint, PAM50/Prosigna, EndoPredict, MapQuant Dx, IHC4, and Theros-Breast Cancer Gene Expression Ratio Assay).

NCCN Guidelines Insights: Breast Cancer, Version 3.2018

These NCCN Guidelines Insights highlight the updated recommendations for use of multigene assays to guide decisions on adjuvant systemic chemotherapy therapy for women with hormone receptor-positive, HER2-negative early-stage invasive breast cancer. This report summarizes these updates and discusses the rationale behind them.

MiR-129-5p induces cell cycle arrest through modulating HOXC10/Cyclin D1 to inhibit gastric cancer progression

MicroRNAs (miRNAs) play important roles in posttranscriptional regulation and may serve as targets for the diagnosis and treatment of cancers. Nevertheless, a comprehensive understanding of miRNAs profiles in gastric cancer progression is still lacking. Here, we report that miR-129-5p is downregulated in gastric cancer by analyzing TCGA database (n = 41) and clinical tumor samples (n = 60). MiR-129-5p transfection suppressed gastric cancer cell proliferation through inducing G1 phase arrest in vitro and inhibit xenograft tumor growth in vivo. MiR-129-5p directly targeted the 3' untranslated regions (3' UTR) of HOXC10 mRNA and downregulated its expression. Importantly, miR-129-5p could reverse the oncogenic effect induced by HOXC10. We systemically screened the downstream target of HOXC10 by ChIP sequencing, and found that HOXC10 could transcriptionally regulate the expression of Cyclin D1 and facilitate G1/S cell cycle transition. Notably, high levels of HOXC10 and Cyclin D1 were related with poor prognosis of gastric cancer patients (n = 90). These findings reveal a novel role of miR-129-5p/HOXC10/Cyclin D1 axis in modulating cell cycle and gastric tumorigenesis, which might provide potential prognostic biomarkers and therapeutic targets for gastric cancer patients.

Available and emerging molecular markers in the clinical management of breast cancer

Introduction: Biomarker assessment is fundamental to managing patients with invasive breast cancer. While the assessment of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 is mandatory for all invasive breast tumors, recent advances in our understanding of tumor biology have uncovered a growing list of clinically relevant biomarkers. Areas covered: In early-stage breast cancer, we focus on dynamic changes in Ki-67 during neoadjuvant endocrine therapy and multigene prognostic assays to guide adjuvant chemotherapy decisions. In advanced breast cancer, we discuss the techniques and clinical relevance of ESR1 and PIK3CA mutations in cell-free DNA and describe therapeutically targetable germline or somatic alterations, with specific focus on BRCA mutations, microsatellite instability, and NTRK fusions. Expert opinion: Biomarkers influence breast cancer management at every stage of disease. This review summarizes recently identified tissue and blood-based biomarkers, implications on clinical management, current limitations and future developments in both early- and advanced-stage breast cancer.

Paralogous HOX13 Genes in Human Cancers

Hox genes (HOX in humans), an evolutionary preserved gene family, are key determinants of embryonic development and cell memory gene program. Hox genes are organized in four clusters on four chromosomal loci aligned in 13 paralogous groups based on sequence homology (Hox gene network). During development Hox genes are transcribed, according to the rule of “spatio-temporal collinearity”, with early regulators of anterior body regions located at the 3’ end of each Hox cluster and the later regulators of posterior body regions placed at the distal 5’ end. The onset of 3’ Hox gene activation is determined by Wingless-type MMTV integration site family (Wnt) signaling, whereas 5’ Hox activation is due to paralogous group 13 genes, which act as posterior-inhibitors of more anterior Hox proteins (posterior prevalence). Deregulation of HOX genes is associated with developmental abnormalities and different human diseases. Paralogous HOX13 genes (HOX A13, HOX B13, HOX C13 and HOX D13) also play a relevant role in tumor development and progression. In this review, we will discuss the role of paralogous HOX13 genes regarding their regulatory mechanisms during carcinogenesis and tumor progression and their use as biomarkers for cancer diagnosis and treatment.

Tumour growth and immune evasion as targets for a new strategy in advanced cancer

It has become clearer that advanced cancer, especially advanced breast cancer, is an entirely displayed pathological system that is much more complex than previously considered. However, the direct relationship between tumour growth and immune evasion can represent a general rule governing the pathological cancer system from the initial cancer cells to when the system is entirely displayed. Accordingly, a refined pathobiological model and a novel therapeutic strategy are proposed. The novel therapeutic strategy is based on therapeutically induced conditions (undetectable tumour burden and/or a prolonged tumour ‘resting state’), which enable an efficacious immune response in advanced breast and other types of solid cancers.

Genes and functions from breast cancer signatures

BACKGROUND

Breast cancer is a heterogeneous disease and personalized medicine is the hope for the improvement of the clinical outcome. Multi-gene signatures for breast cancer stratification have been extensively studied in the past decades and more than 30 different signatures have been reported. A major concern is the minimal overlap of genes among the reported signatures. We investigated the breast cancer signature genes to address our hypothesis that the genes of different signature may share common functions, as well as to use these previously reported signature genes to build better prognostic models.

METHODS

A total of 33 signatures and the corresponding gene lists were investigated. We first examined the gene frequency and the gene overlap in these signatures. Then the gene functions of each signature gene list were analysed and compared by the KEGG pathways and gene ontology (GO) terms. A classifier built using the common genes was tested using the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) data. The common genes were also tested for building the Yin Yang gene mean expression ratio (YMR) signature using public datasets (GSE1456 and GSE2034).

RESULTS

Among a total of 2239 genes collected from the 33 breast cancer signatures, only 238 genes overlapped in at least two signatures; while from a total of 1979 function terms enriched in the 33 signature gene lists, 429 terms were common in at least two signatures. Most of the common function terms were involved in cell cycle processes. While there is almost no common overlapping genes between signatures developed for ER-positive (e.g. 21-gene signature) and those developed for ER-negative (e.g. basal signatures) tumours, they have common function terms such as cell death, regulation of cell proliferation. We used the 62 genes that were common in at least three signatures as a classifier and subtyped 1141 METABRIC cases including 144 normal samples into nine subgroups. These subgroups showed different clinical outcome. Among the 238 common genes, we selected those genes that are more highly expressed in normal breast tissue than in tumours as Yang genes and those more highly expressed in tumours than in normal as Yin genes and built a YMR model signature. This YMR showed significance in risk stratification in two datasets (GSE1456 and GSE2034).

CONCLUSIONS

The lack of significant numbers of overlapping genes among most breast cancer signatures can be partially explained by our discovery that these signature genes represent groups with similar functions. The genes collected from these previously reported signatures are valuable resources for new model development. The subtype classifier and YMR signature built from the common genes showed promising results.

Enrichment of high-grade tumors in breast cancer gene expression studies

Purpose

Gene expression (GE) profiling for breast cancer classification and prognostication has become increasingly used in clinical diagnostics. GE profiling requires a reasonable tumor cell percentage and high-quality RNA. As a consequence, a certain amount of samples drop out. If tumor characteristics are different between samples included and excluded from GE profiling, this can lead to bias. Therefore, we assessed whether patient and tumor characteristics differ between tumors suitable or unsuitable for generating GE profiles in breast cancer.

Methods

In a consecutive cohort of 738 breast cancer patients who received neoadjuvant chemotherapy at the Netherlands Cancer Institute, GE profiling was performed. We compared tumor characteristics and treatment outcome between patients included and excluded from GE profiling. Results were validated in an independent cohort of 812 patients treated with primary surgery.

Results

GE analysis could be performed in 53% of the samples. Patients with tumor GE profiles more often had high-grade tumors [odds ratio 2.57 (95%CI 1.77–3.72), p < 0.001] and were more often lymph node positive [odds ratio 1.50 (95%CI 1.03–2.19), p = 0.035] compared to the group for which GE profiling was not possible. In the validation cohort, tumors suitable for gene expression analysis were more often high grade.

Conclusions

In our gene expression studies, tumors suitable for GE profiling had more often an unfavorable prognostic profile. Due to selection of samples with a high tumor percentage, we automatically select for tumors with specific features, i.e., tumors with a higher grade and lymph node involvement. It is important to be aware of this phenomenon when performing gene expression analysis in a research or clinical context.

Electronic supplementary material

The online version of this article (10.1007/s10549-017-4622-9) contains supplementary material, which is available to authorized users.

Gene Expression Assays for Early-Stage Hormone Receptor-Positive Breast Cancer: Understanding the Differences

Biomarkers are frequently used to guide decisions for treatment of early-stage estrogen (ER) and progesterone (PR) receptor–positive (ER/PR+) invasive breast cancers and have been incorporated into guidelines. The American Society of Clinical Oncology (ASCO) 2016 guideline and a 2017 update were recently published to help clinicians use the tests available. ASCO currently recommends five tests that show evidence of clinical utility based on the parameters defined in the guideline. These include the 21-gene assay (Oncotype DX), Prediction of Analysis of Microarray-50 (PAM50), 12-gene risk score (Endopredict), Breast Cancer Index (BCI), and, most recently, the 70-gene assay (Mammaprint). However, discordance is often seen when the results of these gene assays are compared in a particular patient, for a number of reasons: the assays were initially developed to answer different questions, and the molecular makeup of each signature reflects this; the patient populations that were studied also differed and may not reflect the patient being tested; furthermore, the study design and statistical analysis varied between each test, leading to different scoring scales that may not be comparable. In this review, the background on the development and validation of these assays is discussed, and studies comparing them are reviewed. To provide guidance on which test to choose, the studies that support the level of evidence for clinical utility are presented. However, the choice of a particular test will also be influenced by socioeconomic factors, clinical factors, and patient preferences. We hope that a better understanding of the scientific and clinical rationale for each test will allow patients and providers to make optimal decisions for treatment of early-stage ER/PR+ breast cancer.

A 16 Yin Yang gene expression ratio signature for ER+/node- breast cancer

Breast cancer is one of the leading causes of cancer death in women. It is a complex and heterogeneous disease with different clinical outcomes. Stratifying patients into subgroups with different outcomes could help guide clinical decision making. In this study, we used two opposing groups of genes, Yin and Yang, to develop a prognostic expression ratio signature. Using the METABRIC cohort we identified a16-gene signature capable of stratifying breast cancer patients into four risk levels with intention that low-risk patients would not undergo adjuvant systemic therapy, intermediate-low-risk patients will be treated with hormonal therapy only, and intermediate-high- and high-risk groups will be treated by chemotherapy in addition to the hormonal therapy. The 16-gene signature for four risk level stratifications of breast cancer patients has been validated using 14 independent datasets. Notably, the low-risk group (n = 51) of 205 estrogen receptor-positive and node negative (ER+/node-) patients from three different datasets who had not had any systemic adjuvant therapy had 100% 15-year disease-specific survival rate. The Concordance Index of YMR for ER+/node negative patients is close to the commercially available signatures. However, YMR showed more significance (HR = 3.7, p = 8.7e-12) in stratifying ER+/node- subgroup than OncotypeDx (HR = 2.7, p = 1.3e-7), MammaPrint (HR = 2.5, p = 5.8e-7), rorS (HR = 2.4, p = 1.4e-6), and NPI (HR = 2.6, p = 1.2e-6). YMR signature may be developed as a clinical tool to select a subgroup of low-risk ER+/node- patients who do not require any adjuvant hormonal therapy (AHT).

Selecting postoperative adjuvant systemic therapy for early stage breast cancer: A critical assessment of commercially available gene expression assays

Risk stratification of patients with early stage breast cancer may support adjuvant chemotherapy decision-making. This review details the development and validation of six multi-gene classifiers, each of which claims to provide useful prognostic and possibly predictive information for early stage breast cancer patients. A careful assessment is presented of each test's analytical validity, clinical validity, and clinical utility, as well as the quality of evidence supporting its use.

Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer

PURPOSE

To examine the effect of intratumor heterogeneity (ITH) on detection of genes within gene expression panels (GEPs) and the subsequent ability to predict prognostic risk.

EXPERIMENTAL DESIGN

Multiplexed barcoded RNA analysis was used to measure the expression of 141 genes from five GEPs (Oncotype Dx, MammaPrint, PAM50, EndoPredict, and Breast Cancer Index) in breast cancer tissue sections and tumor-rich cores from 71 estrogen receptor (ER)-positive node-negative tumors, on which clinical Oncotype Dx testing was previously performed. If the tumor had foci of high Ki67 (n = 26), low/negative progesterone receptor (PR; n = 13), or both (n = 5), additional cores were obtained. In total, 181 samples were processed. Oncotype Dx recurrence scores were calculated from NanoString nCounter gene expression data.

RESULTS

Hierarchical clustering using all GEP genes showed that majority (61 of 71) of tumor samples clustered by patient, indicating greater interpatient heterogeneity (IPH) than ITH. We found a strikingly high correlation between Oncotype Dx recurrence scores obtained from whole sections versus tumor-rich cores (r = 0.94). However, high Ki67 and low PR cores had slightly higher but not statistically significant recurrence scores. For 18 of 71 (25%) patients, scores were divergent between sections and cores and crossed the boundaries for low, intermediate, and high risk.

CONCLUSIONS

Our study indicates that in patients with highly heterogeneous tumors, GEP recurrence scores from a single core could under- or overestimate prognostic risk. Hence, it may be a useful strategy to assess multiple samples (both representative and atypical cores) to fully account for the ITH-driven variation in risk prediction. Clin Cancer Res; 22(21); 5362-9. ©2016 AACR.

HOX genes: Major actors in resistance to selective endocrine response modifiers

Long term treatment with therapies aimed at blocking the estrogen- (ER) or androgen receptor (AR) action often leads to the development of resistance to selective modulators of the estrogen receptor (SERMs) in ERα-positive breast cancer, or of the androgen receptor (SARMs) in AR-positive prostate cancer. Many underlying molecular events that confer resistance are known, but a unifying theme is yet to be revealed. Receptor tyrosine kinases (RTKs) such EGFR, ERBB2 and IGF1R are major mediators that can directly alter cellular response to the SERM, tamoxifen, but the mechanisms underlying increased expression of RTKs are not clear. A number of HOX genes and microRNAs and non-coding RNAs residing in the HOX cluster, have been identified as important independent predictors of endocrine resistant breast cancer. Recently, convincing evidence has accumulated that several members belonging to the four different HOX clusters contribute to endocrine therapy resistant breast cancer, but the mechanisms remain obscure. In this article, we have reviewed recent progress in understanding of the functioning of HOX genes and regulation of their expression by hormones. We also discuss, in particular, the contributions of several members of the HOX gene family to endocrine resistant breast cancer.

Tailoring Chemotherapy in Early-Stage Breast Cancer: Based on Tumor Biology or Tumor Burden?

The question of whether to offer adjuvant chemotherapy to patients with early-stage breast cancer has always been challenging to answer. It is well known that a substantial proportion of patients with early-stage breast cancer are over treated, especially when staging and hormonal and HER2 receptors are solely taken into consideration. The advances in our knowledge of breast cancer biology and its clinical implications were the basis for the discovery of additional reliable prognostic markers to aid decision making for adjuvant treatment. Gene expression profiling is a molecular tool that more precisely defines the intrinsic characteristics of each individual tumor. The application of this technology has led to the development of gene signatures/profiles with relevant prognostic-and some predictive-value that have become important tools in defining which patients with early-stage breast cancer can be safely spared from chemotherapy. However, the exact clinical utility of these tools will only be determined after the results of two large prospective randomized trials, MINDACT and TailorX, evaluating their role become available. Notwithstanding the existence of these genomic tools, tumor burden (defined as tumor size and nodal status) still has independent prognostic value and must be incorporated in decision making. In addition, these gene signatures have limited predictive value, and new biomarkers and new targets are needed. Therefore close collaboration between clinicians and scientists is crucial. Lastly, issues of cost-effectiveness, reimbursement, and availability are crucial and widely variable around the globe.

EN2 in Prostate Cancer

Despite extensive efforts to identify a clinically useful diagnostic biomarker in prostate cancer, no new test has been approved by regulatory authorities. As a result, this unmet need has shifted to biomarkers that additionally indicate presence or absence of "significant" disease. EN2 is a homeodomain-containing transcription factor secreted by prostate cancer into the urine and can be detected by enzyme-linked immunoassay. EN2 may be an ideal biomarker because normal prostate tissue and benign prostatic hypertrophic cells do not secrete EN2. This review discusses the enormous potential of EN2 to address this unmet need and provide the urologist with a simple, inexpensive, and reliable prostate cancer biomarker.

Role of single nucleotide polymorphisms in pharmacogenomics and their association with human diseases

Global statistical data shed light on an alarming trend that every year thousands of people die due to adverse drug reactions as each individual responds in a different way to the same drug. Pharmacogenomics has come up as a promising field in drug development and clinical medication in the past few decades. It has emerged as a ray of hope in preventing patients from developing potentially fatal complications due to adverse drug reactions. Pharmacogenomics also minimizes the exposure to drugs that are less/non-effective and sometimes even found toxic for patients. It is well reported that drugs elicit different responses in different individuals due to variations in the nucleotide sequences of genes encoding for biologically important molecules (drug-metabolizing enzymes, drug targets and drug transporters). Single nucleotide polymorphisms (SNPs), the most common type of polymorphism found in the human genome is believed to be the main reason behind 90% of all types of genetic variations among the individuals. Therefore, pharmacogenomics may be helpful in answering the question as to how inherited differences in a single gene have a profound effect on the mobilization and biological action of a drug. In the present review, we have discussed clinically relevant examples of SNP in associated diseases that can be utilized as markers for "better management of complex diseases" and attempted to correlate the drug response with genetic variations. Attention is also given towards the therapeutic consequences of inherited differences at the chromosomal level and how associated drug disposition and/or drug targets differ in various diseases as well as among the individuals.

Identification of patients with hormone receptor-positive breast cancer who need adjuvant tamoxifen therapy for more than 5 years

BACKGROUND/PURPOSE

Extended hormonal therapy with tamoxifen for > 5 years has improved disease-free survival (DFS) and overall survival (OS) in hormone receptor (HR)-positive breast cancer patients. The aim of this study was to identify the HR-positive breast cancer women who need adjuvant tamoxifen for > 5 years.

METHODS

Between 1990 and 2004, 1104 HR-positive breast cancer patients who had received tamoxifen treatment at our institution and had been disease free for at least 6 years were included in this analysis. Univariate and multivariate analyses of prognostic factors for late recurrence were performed using the binary logistic regression model.

RESULTS

During a median follow-up period of 10.9 years after surgery, 70 patients died and 99 showed recurrence. In multivariate analysis, age < 40 years (p < 0.001) and lymph node metastasis (p < 0.001) were associated with higher rates of recurrence. We stratified patients into high-risk (age < 40 years or positive lymph node status, 536 patients) and low-risk (age > 40 years and negative lymph node status, 566 patients) groups. The recurrence rates were 14.6% and 3.5% in the high-risk and low-risk groups, respectively. Patients in the high-risk group had poorer disease-free survival (p < 0.001) and overall survival (p = 0.010) than those in the low-risk group.

CONCLUSION

Our findings suggest that HR-positive breast cancer women either aged < 40 years or with positive lymph node status were justified in continuing with tamoxifen therapy for > 5 years.

Loss of heterozygosity at the CYP2D6 locus in breast cancer: implications for germline pharmacogenetic studies

BACKGROUND

Controversy exists regarding the impact of CYP2D6 genotype on tamoxifen responsiveness. We examined loss of heterozygosity (LOH) at the CYP2D6 locus and determined its impact on genotyping error when tumor tissue is used as a DNA source.

METHODS

Genomic tumor data from the adjuvant and metastatic settings (The Cancer Genome Atlas [TCGA] and Foundation Medicine [FM]) were analyzed to characterize the impact of CYP2D6 copy number alterations (CNAs) and LOH on Hardy Weinberg equilibrium (HWE). Additionally, we analyzed CYP2D6 *4 genotype from formalin-fixed paraffin-embedded (FFPE) tumor blocks containing nonmalignant tissue and buccal (germline) samples from patients on the North Central Cancer Treatment Group (NCCTG) 89-30-52 tamoxifen trial. All statistical tests were two-sided.

RESULTS

In TCGA samples (n =627), the CYP2D6 LOH rate was similar in estrogen receptor (ER)-positive (41.2%) and ER-negative (35.2%) but lower in HER2-positive tumors (15.1%) (P < .001). In FM ER+ samples (n = 290), similar LOH rates were observed (40.8%). In 190 NCCTG samples, the agreement between CYP2D6 genotypes derived from FFPE tumors and FFPE tumors containing nonmalignant tissue was moderate (weighted Kappa = 0.74; 95% CI = 0.63 to 0.84). Comparing CYP2D6 genotypes derived from buccal cells to FFPE tumor DNA, CYP2D6*4 genotype was discordant in six of 31(19.4%). In contrast, there was no disagreement between CYP2D6 genotypes derived from buccal cells with FFPE tumors containing nonmalignant tissue.

CONCLUSIONS

LOH at the CYP2D6 locus is common in breast cancer, resulting in potential misclassification of germline CYP2D6 genotypes. Tumor DNA should not be used to determine germline CYP2D6 genotype without sensitive techniques to detect low frequency alleles and quality control procedures appropriate for somatic DNA.

Endocrine Resistance in Breast Cancer

Around 70% of all breast cancers are estrogen receptor alpha positive and hence their development is highly dependent on estradiol. While the invention of endocrine therapies has revolusioned the treatment of the disease, resistance to therapy eventually occurs in a large number of patients. This paper seeks to illustrate and discuss the complexity and heterogeneity of the mechanisms which underlie resistance and the approaches proposed to combat them. It will also focus on the use and development of methods for predicting which patients are likely to develop resistance.

Late recurrences in early breast cancer: for whom and how long is endocrine therapy beneficial?

During the last decade, besides the well-established clinical-pathological predictors for the risk of late recurrence in breast cancer, such as estrogen receptor status, and T and N stage, a variety of multigene assays have been shown to improve prognostication and prediction in this setting. Several clinical trials have evaluated the role of extended endocrine therapy with tamoxifen (ATLAS) or aromatase inhibitors (MA.17, NSABP-B33 and ABCSG 6a), and other randomized studies are still ongoing. However, among this patient population, it is still not clear who could benefit from extended therapy and what the optimal treatment duration should be. New multigene assays such as EndoPredict, PAM50 ROR-score, HOXB13/IL17BR ratio and Breast Cancer Index provide significant and relevant prognostic information concerning the likelihood of recurrence beyond 5 years after surgery. The identified low-risk subgroups not only show a very favorable prognosis, they also seem to have only little benefit from extended aromatase inhibitor therapy. Many of these reverse transcriptase/polymerase chain reaction-based techniques have been validated in archived tumor material from large phase III trials, and will soon be available to routine pathology laboratories as an aid in clinical decision-making for patients.

EN2: a novel prostate cancer biomarker

Extensive efforts to identify a clinically useful biomarker for the diagnosis of prostate cancer have resulted in important insights into the biology of the disease, but no new test has been approved by regulatory authorities. The unmet need has also shifted to identifying biomarkers that not only diagnose prostate cancer but also indicate whether the patient has 'significant' disease. EN2 is a homeobox-containing transcription factor secreted specifically by prostate cancers into urine, where it can be detected by a simple ELISA assay. A number of studies have demonstrated the enormous potential of EN2 to address this unmet need and provide the urologist with a simple, cheap and efficient prostate cancer biomarker.

The HOXB13:IL17BR biomarker: prognostic for late recurrence and predictive for benefit from endocrine therapy

SUMMARY Estrogen receptor-positive breast cancer accounts for more than two-thirds of breast cancer cases. While much attention has been focused on metastatic recurrence during the first 5 years following diagnosis, more than half of distant recurrences occur beyond 5 years. Several studies have demonstrated significant patient benefit for extended adjuvant therapy, but there is a clinical need for biomarkers that can identify patients who are at risk for late distant recurrence and would benefit from extended therapy. The HOXB13:IL17BR gene-expression ratio has been repeatedly validated as a prognostic breast cancer biomarker that estimates risk independent of clinicopathological factors, including tumor grade. Recent studies have revealed that the HOXB13:IL17BR ratio is both prognostic for late recurrences and predictive for endocrine therapy response.

Genomic profiling in luminal breast cancer

The developments in gene expression analysis have made it possible to sub-classify hormone receptor-positive (luminal) breast cancer in different prognostic subgroups. This sub-classification is currently used in clinical routine as prognostic signature (e.g. 21-gene Onoctype DX®, 70-gene Mammaprint®). As yet, the optimal method for sub-classification has not been defined. Moreover, there is no evidence from prospective trials. This review explores widely used genomic signatures in luminal breast cancer, making a critical appraisal of evidence from retrospective/prospective trials. It is based on systematic literature search performed using Medline (accessed September 2013) and abstracts presented at the Annual Meeting of American Society of Clinical Oncology and San Antonio Breast Cancer Symposium.

Two-gene expression ratio as predictor for breast cancer treated with tamoxifen: evidence from meta-analysis

A HOXB13-to-IL17BR expression ratio was previously identified to predict a clinical outcome of breast cancer patients treated with adjuvant tamoxifen. A large number of studies were addressed to confirm its function as a predictor of breast cancer outcome treated with tamoxifen. However, conflicting results were got. In this study, a systematic search of databases was carried out, and other relevant papers were also identified. Then, the analyses were conducted according to the PRISMA and MOOSE guidelines. After full review, 11 studies with a total of 2,958 participants were deemed eligible and were included in the study. Pooled results revealed that women with higher HOXB13-to-IL17BR expression ratio had significantly worse outcomes in breast patients treated with tamoxifen, especially for those who are negative of node.

Yin Yang gene expression ratio signature for lung cancer prognosis

Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient's prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.

Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker

BACKGROUND

Biomarkers to optimize extended adjuvant endocrine therapy for women with estrogen receptor (ER)-positive breast cancer are limited. The HOXB13/IL17BR (H/I) biomarker predicts recurrence risk in ER-positive, lymph node-negative breast cancer patients. H/I was evaluated in MA.17 trial for prognostic performance for late recurrence and treatment benefit from extended adjuvant letrozole.

METHODS

A prospective-retrospective, nested case-control design of 83 recurrences matched to 166 nonrecurrences from letrozole- and placebo-treated patients within MA.17 was conducted. Expression of H/I within primary tumors was determined by reverse-transcription polymerase chain reaction with a prespecified cutpoint. The predictive ability of H/I for ascertaining benefit from letrozole was determined using multivariable conditional logistic regression including standard clinicopathological factors as covariates. All statistical tests were two-sided.

RESULTS

High H/I was statistically significantly associated with a decrease in late recurrence in patients receiving extended letrozole therapy (odds ratio [OR] = 0.35; 95% confidence interval [CI] = 0.16 to 0.75; P = .007). In an adjusted model with standard clinicopathological factors, high H/I remained statistically significantly associated with patient benefit from letrozole (OR = 0.33; 95% CI = 0.15 to 0.73; P = .006). Reduction in the absolute risk of recurrence at 5 years was 16.5% for patients with high H/I (P = .007). The interaction between H/I and letrozole treatment was statistically significant (P = .03).

CONCLUSIONS

In the absence of extended letrozole therapy, high H/I identifies a subgroup of ER-positive patients disease-free after 5 years of tamoxifen who are at risk for late recurrence. When extended endocrine therapy with letrozole is prescribed, high H/I predicts benefit from therapy and a decreased probability of late disease recurrence.

Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence

PURPOSE

Residual risk of relapse remains a substantial concern for patients with hormone receptor-positive breast cancer, with approximately half of all disease recurrences occurring after five years of adjuvant antiestrogen therapy.

EXPERIMENTAL DESIGN

The objective of this study was to examine the prognostic performance of an optimized model of Breast Cancer Index (BCI), an algorithmic gene expression-based signature, for prediction of early (0-5 years) and late (>5 years) risk of distant recurrence in patients with estrogen receptor-positive (ER(+)), lymph node-negative (LN(-)) tumors. The BCI model was validated by retrospective analyses of tumor samples from tamoxifen-treated patients from a randomized prospective trial (Stockholm TAM, n = 317) and a multi-institutional cohort (n = 358).

RESULTS

Within the Stockholm TAM cohort, BCI risk groups stratified the majority (∼65%) of patients as low risk with less than 3% distant recurrence rate for 0 to 5 years and 5 to 10 years. In the multi-institutional cohort, which had larger tumors, 55% of patients were classified as BCI low risk with less than 5% distant recurrence rate for 0 to 5 years and 5 to 10 years. For both cohorts, continuous BCI was the most significant prognostic factor beyond standard clinicopathologic factors for 0 to 5 years and more than five years.

CONCLUSIONS

The prognostic sustainability of BCI to assess early- and late-distant recurrence risk at diagnosis has clinical use for decisions of chemotherapy at diagnosis and for decisions for extended adjuvant endocrine therapy beyond five years.

In silico discovery of mitosis regulation networks associated with early distant metastases in estrogen receptor positive breast cancers

The aim of this study was to perform comparative analysis of multiple public datasets of gene expression in order to identify common genes as potential prognostic biomarkers. Additionally, the study sought to identify biological processes and pathways that are most significantly associated with early distant metastases (<5 years) in women with estrogen receptor-positive (ER+) breast tumors. Datasets from three published studies were selected for in silico analysis of gene expression profiles of ER+ breast cancer, using time to distant metastasis as the clinical endpoint. A subset of 44 differently expressed genes (DEGs) was found common to all three studies and characterized by mitotic checkpoint genes and pathways that regulate mitotic spindle and chromosome dynamics. DEG promoter regions were enriched with NFY binding sites. Analysis of miRNA target sites identified significant enrichment of miR-192, miR-193B, and miR-16-1 targets. Aberrant mitotic regulation could drive increased genomic instability leading to a progression towards an early onset metastatic phenotype. The relative importance of mitotic instability may reflect the clinical utility of mitotic poisons in metastatic breast cancer, including poisons such as the taxanes, epothilones, and vinca alkaloids.

Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients: a DBCG study

Background

Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamoxifen mono-therapy.

Methodology/Principal Findings

Post-menopausal breast cancer patients diagnosed no later than 2002, being ER+ as defined by >1% IHC staining and having a frozen tumor sample with >50% tumor content were included. Tumor samples from 108 patients treated with adjuvant Tamoxifen were analyzed for the expression of 59 genes using quantitative-PCR. End-point was clinically verified recurrence to distant organs or ipsilateral breast. Gene profiles were identified using a model building procedure based on conditional logistic regression and leave-one-out cross-validation, followed by a non-parametric bootstrap (1000x re-sampling). The optimal profiles were further examined in 5 previously-reported datasets containing similar patient populations that were either treated with Tamoxifen or left untreated (n = 623). Three gene signatures were identified, the strongest being a 2-gene combination of BCL2-CDKN1A, exhibiting an accuracy of 75% for prediction of outcome. Independent examination using 4 previously-reported microarray datasets of Tamoxifen-treated patient samples (n = 503) confirmed the potential of BCL2-CDKN1A. The predictive value was further determined by comparing the ability of the genes to predict recurrence in an additional, previously-published, cohort consisting of Tamoxifen-treated (n = 58, p = 0.015) and untreated patients (n = 62, p = 0.25).

Conclusions/Significance

A novel gene expression signature predictive of outcome of Tamoxifen-treated patients was identified. The validation suggests that BCL2-CDKN1A exhibit promising predictive potential.

Molecular profiling for stage II colon cancer

SUMMARY Although nearly 80% of patients with stage II colon cancer are cured by surgery alone, 20% will relapse. One major challenge is to identify individuals who will derive enough benefit from adjuvant therapy to balance the risks, costs and inconvenience. Existing markers, such as microsatellite instability, are predictive and prognostic, but only apply to a small number of patients. Novel technologies that include molecular profiling are emerging tools that may help to identify patients at high risk for recurrence or predict who will derive a greater benefit from adjuvant treatment. This article reviews molecular markers in stage II colon cancer and their potential role in identification of high-risk patients.

Extended adjuvant endocrine therapy in hormone dependent breast cancer: the paradigm of the NCIC-CTG MA.17/BIG 1-97 trial

Early hormone-receptor-positive breast cancer is a chronic relapsing disease that can remain clinically silent for many years. The NCIC-CTG MA.17/BIG 1-97 trial randomized disease-free early breast cancer patients who had received five years of adjuvant tamoxifen to either letrozole or placebo and was the first to demonstrate a benefit with extended endocrine therapy. MA.17/BIG 1-97 was stopped at the first interim analysis because disease free survival was strongly prolonged in the letrozole arm. Subsequent subset analyses and longer follow up have shown that this therapy improved survival across all groups, particularly among women with node-positive disease and those that were pre-menopausal at time of study enrolment. The MA.17/BIG 1-97 study should be considered a paradigm for extended adjuvant endocrine therapy in hormone-receptor-positive early breast cancer.

GREB1 functions as a growth promoter and is modulated by IL6/STAT3 in breast cancer

Background

Growth Regulation by Estrogen in Breast cancer (GREB1) was an estrogen receptor (ER) target gene, and GREB1 expression inversely correlated with HER2 status, possibly as a surrogate marker for ER status and a predictor for tamoxifen resistance in breast cancer patients. In the present study, we examine the function and regulation of GREB1 in breast cancer, with the goal to develop GREB1 as a biomarker in breast cancer with de novo and acquired tamoxifen resistance.

Methods

We overexpressed GREB1 using adenovirus containing the full length GREB1 cDNA (Ad-GREB1) in breast cancer cell lines. The soft agar assay was used as a measure of anchorage independent growth. The effects of GREB1 on cell proliferation in MCF-7 cells transduced with Ad-GREB1 were also measured by the me olic activity using AlamarBlue assay. We tested whether there was interaction between STAT3 and ER, which could repress GREB1 expression by immunoprecipitation assay. The effects of IL-6/JAK/STAT3 cascade activation on estrogen-induced GREB1 promoter activity were determined by luciferase assay and those on gene expression were measured by real time reverse transcription polymerase chain reaction (qRT-PCR).

Results

We found that the ability of breast cancer cells to grow in soft agar is enhanced following GREB1 transfection. In MCF-7 cells transduced with Ad-GREB1 or transfected with siRNA GREB1, the metabolic activity was increased or completely abolished, suggesting that GREB1 may function as a growth promoter in breast cancer. E2 treatment increased GREB1 promoter luciferase activity. IL-6 inhibited E2-induced GREB1 transcription activity and GREB1 mRNA expression. Constitutively expressing active STAT3 construct (STAT3-C) dramatically decreased GREB1 transcription.

Conclusions

These data indicate that overexpression of GREB1 promotes cell proliferation and increases the clonogenic ability in breast cancer cells. Moreover, Il6/STAT3 modulates estrogen-induced GREB1 transcriptional activity in breast cancer cells.

Analysis of the Hox epigenetic code

Archetypes of histone modifications associated with diverse chromosomal states that regulate access to DNA are leading the hypothesis of the histone code (or epigenetic code). However, it is still not evident how these post-translational modifications of histone tails lead to changes in chromatin structure. Histone modifications are able to activate and/or inactivate several genes and can be transmitted to next generation cells due to an epigenetic memory. The challenging issue is to identify or “decrypt” the code used to transmit these modifications to descent cells. Here, an attempt is made to describe how histone modifications operate as part of histone code that stipulates patterns of gene expression. This papers emphasizes particularly on the correlation between histone modifications and patterns of Hox gene expression in Caenorhabditis elegans. This work serves as an example to illustrate the power of the epigenetic machinery and its use in drug design and discovery.

Regulatory approval pathways for molecular diagnostic technology

This chapter describes the basic categories for regulatory approval to sell/market a molecular profiling technology. The US Food and Drug Administration regulates and provides guidance, for marketing in vitro diagnostic devices (IVD). Three different paths currently exist for obtaining Food and Drug Administration (FDA) approval of an IVD: (a) If the new test can be shown to be substantially equivalent to an existing predicate test on the market, then the 510(k) is the regulatory path for new device approval. (b) If your new diagnostic technology cannot be considered substantially equivalent to an existing technology, and will be used to make a critical medical decision concerning the diagnosis, treatment, or medical management, then the premarket approval (PMA) is the regulatory path of choice. (c) If no predicate device exists and the test is of low or moderate risk, it may be eligible for a de novo reclassification. If the test is done "in house," in the designated laboratory only, for a patient sample that is sent to the laboratory from an outside physician's office or medical facility, then the test can be potentially marketed under "home brew" guidelines (also known as laboratory developed tests) regulated under the Clinical Laboratory Improvement Amendments (CLIA). The Centers for Medicare and Medicaid Services (CMS) assumes primary responsibility for financial management operations of the CLIA program, but the categorization of commercially marketed in vitro diagnostic tests under CLIA is the responsibility of the FDA. Definitions, guidelines, information sources, and instructions for data requirements are outlined for each regulatory pathway.

Integrating Breast Cancer Genetics into Clinical Practice

Breast cancer prognosis and treatment is guided by traditional clinicopathological parameters and individual molecular markers. Despite the remarkable advances in our scientific understanding of breast cancer genetics, the impact of such information on medical care has, to date, been modest. Although the use of simple genetics is already in vogue in clinical practice, the concept of molecular profiling and multiparameter gene classifiers was raised after the introduction of the high-throughput gene expression microarrays. This technology, in addition to highlighting the molecular heterogeneity of breast cancer, has led to the development of prognostic and predictive gene signatures. Studies are underway to assess the clinical validity and clinical utility of these multigene assays and their incorporation into clinical practice. This article reviews the current status and projected future use of genetics and genomics in breast cancer management and their impact on the refinement of risk stratification to permit individualized and patient-tailored therapy. Limitations based on our current scientific understanding and realistic expectations are also explored.

Early developments in gene-expression profiling of breast tumors: potential for increasing black-white patient disparities in breast cancer outcomes?

New prognostic tests, such as gene-expression profiling (GEP) of breast tumors, are expected to prolong survival and improve the quality of life for many breast cancer patients. In this article, we argue that GEP has not been adequately validated in minority populations, and that both biological and social factors might affect the broad utility of these tests in diverse populations. We suggest that the widespread use of this technology could potentially lead to suboptimal treatment for black women, resulting in a further increase in black-white patient disparities in treatment response, morbidity and mortality rates. We argue for the need to build a large and diverse evidence base for GEP and other emerging technologies in personalized medicine.

Interleukins, from 1 to 37, and interferon-γ: receptors, functions, and roles in diseases

Advancing our understanding of mechanisms of immune regulation in allergy, asthma, autoimmune diseases, tumor development, organ transplantation, and chronic infections could lead to effective and targeted therapies. Subsets of immune and inflammatory cells interact via ILs and IFNs; reciprocal regulation and counter balance among T(h) and regulatory T cells, as well as subsets of B cells, offer opportunities for immune interventions. Here, we review current knowledge about ILs 1 to 37 and IFN-γ. Our understanding of the effects of ILs has greatly increased since the discoveries of monocyte IL (called IL-1) and lymphocyte IL (called IL-2); more than 40 cytokines are now designated as ILs. Studies of transgenic or knockout mice with altered expression of these cytokines or their receptors and analyses of mutations and polymorphisms in human genes that encode these products have provided important information about IL and IFN functions. We discuss their signaling pathways, cellular sources, targets, roles in immune regulation and cellular networks, roles in allergy and asthma, and roles in defense against infections.

The molecular mechanisms underlying the pharmacological actions of ER modulators: implications for new drug discovery in breast cancer

Our understanding of the molecular mechanisms underlying the pharmacological actions of estrogen receptor (ER) ligands has evolved considerably in recent years. Much of this knowledge has come from a detailed dissection of the mechanism(s) of action of the Selective Estrogen Receptor Modulators (SERMs) tamoxifen and raloxifene, so called for their ability to function as ER agonists or antagonists depending on the tissue in which they operate. These mechanistic insights have had a significant impact on the discovery of second generation SERMs, some of which are in late stage clinical development for the treatment/prevention of breast cancer as well as other estrogenopathies. In addition to the SERMs, however, have emerged the Selective Estrogen Degraders (SERDs), which as their name suggests, interact with and facilitate ER turnover in cells. One drug of this class, fulvestrant, has been approved as a third line treatment for ER-positive metastatic breast cancer. Whereas the first generation SERMs/SERDs were discovered in a serendipitous manner, this review will highlight how our understanding of the molecular pharmacology of ER ligands has been utilized in the development of the next generation of SERMs/SERDs, some of which are likely to have a major impact on the pharmacotherapy of breast cancer.

Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial

Background:

A dichotomous index combining two gene expression assays, HOXB13 : IL17BR (H : I) and molecular grade index (MGI), was developed to assess risk of recurrence in breast cancer patients. The study objective was to demonstrate the prognostic utility of the combined index in early-stage breast cancer.

Methods:

In a blinded retrospective analysis of 588 ER-positive tamoxifen-treated and untreated breast cancer patients from the randomised prospective Stockholm trial, H : I and MGI were measured using real-time RT–PCR. Association with patient outcome was evaluated by Kaplan–Meier analysis and Cox proportional hazard regression. A continuous risk index was developed using Cox modelling.

Results:

The dichotomous H : I+MGI was significantly associated with distant recurrence and breast cancer death. The >50% of tamoxifen-treated patients categorised as low-risk had <3% 10-year distant recurrence risk. A continuous risk model (Breast Cancer Index (BCI)) was developed with the tamoxifen-treated group and the prognostic performance tested in the untreated group was 53% of patients categorised as low risk with an 8.3% 10-year distant recurrence risk.

Conclusion:

Retrospective analysis of this randomised, prospective trial cohort validated the prognostic utility of H : I+MGI and was used to develop and test a continuous risk model that enables prediction of distant recurrence risk at the patient level.