Prediction of adjuvant chemotherapy benefit in endocrine responsive, early breast cancer using multigene assays

Selection of Patients With Early-Stage Breast Cancer for Extended Endocrine Therapy: A Secondary Analysis of the IDEAL Randomized Clinical Trial

Importance

There is a need for biomarkers that predict late recurrence risk and extended endocrine therapy (EET) benefit among patients with early-stage breast cancer (EBC). MammaPrint, a 70-gene expression risk-of-recurrence assay, has been found to project significant EET benefit in patients with assay-classified low-risk tumors.

Objective

To determine the test's utility in identifying which patients with EBC in the IDEAL (Investigation on the Duration of Extended Adjuvant Letrozole) trial could benefit from 5-year vs 2.5-year letrozole treatment.

Design, Setting, and Participants

This secondary analysis of the IDEAL randomized clinical trial evaluated postmenopausal women with hormone receptor-positive EBC who were assigned to either 2.5 or 5 years of EET, with 10 years of follow-up after randomization. A 70-gene assay was used to classify tumors as high, low, or ultralow risk. Adverse event (AE) frequency and treatment compliance were evaluated. Statistical analyses were performed from April 2022 to September 2024.

Interventions

After 5 years of endocrine therapy, patients were randomized to 2.5 or 5 years of EET with letrozole.

Main Outcomes and Measures

Primary end point was distant recurrence (DR). Cox proportional hazard regression models and likelihood ratios tested the interaction between treatment and gene expression assay.

Results

Among 515 women included (mean [SD] age at randomization, 59.9 [9.5] years), 265 were in the 2.5-year treatment arm and 250 in the 5-year treatment arm. Of these patients, 223 (43.3%) patients with 70-gene assay-classified low-risk tumors had a significant absolute benefit of 10.1% for DR (hazard ratio, 0.32; 95% CI, 0.12-0.87; P = .03). Treatment interaction was not significant for DR. Of patients with either 70-gene assay-classified high-risk tumors (259 [50.3%]) or ultralow risk tumors (33 [6.4%]), 5 years vs 2.5 years of EET was not associated with improved benefit for DR. As expected, rates of AEs and treatment discontinuation were comparable among the different 70-gene assay risk groups in each treatment arm.

Conclusions and Relevance

This secondary analysis of the IDEAL trial found that the 70-gene assay identified patients with low-risk tumors who could benefit from 5-year vs 2.5-year EET. These findings suggest that this gene expression assay could go beyond guiding neoadjuvant and adjuvant chemotherapy decisions to informing the optimal duration of adjuvant endocrine therapy.

Trial Registration

EU Clinical Trials Register Eudra CT: 2006-003958-16.

Optimizer's dilemma: optimization strongly influences model selection in transcriptomic prediction

Motivation

Most models can be fit to data using various optimization approaches. While model choice is frequently reported in machine-learning-based research, optimizers are not often noted. We applied two different implementations of LASSO logistic regression implemented in Python's scikit-learn package, using two different optimization approaches (coordinate descent, implemented in the liblinear library, and stochastic gradient descent, or SGD), to predict mutation status and gene essentiality from gene expression across a variety of pan-cancer driver genes. For varying levels of regularization, we compared performance and model sparsity between optimizers.

Results

After model selection and tuning, we found that liblinear and SGD tended to perform comparably. liblinear models required more extensive tuning of regularization strength, performing best for high model sparsities (more nonzero coefficients), but did not require selection of a learning rate parameter. SGD models required tuning of the learning rate to perform well, but generally performed more robustly across different model sparsities as regularization strength decreased. Given these tradeoffs, we believe that the choice of optimizers should be clearly reported as a part of the model selection and validation process, to allow readers and reviewers to better understand the context in which results have been generated.

Availability and implementation

The code used to carry out the analyses in this study is available at https://github.com/greenelab/pancancer-evaluation/tree/master/01_stratified_classification. Performance/regularization strength curves for all genes in the Vogelstein et al. (2013) dataset are available at https://doi.org/10.6084/m9.figshare.22728644.

Survival Benefit of Adjuvant Chemotherapy in Node-Positive Breast Cancer With a 21-Gene Recurrence Score of 14 to 25: A Real-World Study Based on the Inverse Probability of Treatment Weighting Method

INTRODUCTION

The role of recurrence score in predicting the benefits of adjuvant chemotherapy for lymph-node-positive breast cancer remains uncertain. We studied chemotherapy usage in patients with 1 to 3 positive lymph nodes and a recurrence score (RS) of 25 or lower to assess changes in clinical practice based on the RxPONDER trial.

METHODS

A retrospective study using the SEER database identified female patients diagnosed with ER-positive, HER2-negative breast cancer, 1 to 3 positive lymph nodes, and an RS of 25 or lower between 2010 and 2015. Patients were divided into nonchemotherapy and chemotherapy groups, with propensity score weighting to balance clinicopathologic factors.

RESULTS

Among 7965 patients, 5774 (72.5%) were in the nonchemotherapy group, while 2191 (27.5%) were in the chemotherapy group. Median follow-up was 39 months. Breast cancer accounted for 67 deaths, while 128 deaths were due to other causes. The weighted 5-year overall survival (OS) rates were 95.7% for the nonchemotherapy group and 97.2% for the chemotherapy group. For high-risk patients, the weighted 5-year OS rates were 95.2% and 97.0% for the nonchemotherapy and chemotherapy groups, respectively, with a significant absolute difference of 1.8% (P = .014). Multivariate analysis showed a significant difference in weighted hazard ratios for OS between the nonchemotherapy and chemotherapy groups in high-risk patients (hazard ratio: 0.64; 95% CI: 0.48-0.86). However, there were no significant differences in weighted hazard ratios for lower-risk patients, and similar results were observed for breast cancer-specific survival (BCSS).

CONCLUSION

Patients with ER-positive, HER2-negative breast cancer and 1 to 3 positive lymph nodes, assessed by a 21-gene RS of 0 to 25, exhibited heterogeneous prognosis. Adjuvant chemotherapy provided a significant survival benefit, especially for patients with RS of 14 to 25, particularly those with invasive ductal carcinoma (IDC) and 2 to 3 positive lymph nodes.

Determinants of response to CDK4/6 inhibitors in the real-world setting

Despite widespread use and a known mechanism of action for CDK4/6 inhibitors in combination with endocrine therapy, features of disease evolution and determinants of therapeutic response in the real-world setting remain unclear. Here, a cohort of patients treated with standard-of-care combination regimens was utilized to explore features of disease and determinants of progression-free survival (PFS) and overall survival (OS). In this cohort of 280 patients, >90% of patients were treated with palbociclib in combination with either an aromatase inhibitor (AI) or fulvestrant (FUL). Most of these patients had modified Scarff-Bloom-Richardson (SBR) scores, and ER, HER2, and PR immunohistochemistry. Both the SBR score and lack of PR expression were associated with shorter PFS in patients treated with AI combinations and remained significant in multivariate analyses (HR = 3.86, p = 0.008). Gene expression analyses indicated substantial changes in cell cycle and estrogen receptor signaling during the course of treatment. Furthermore, gene expression-based subtyping indicated that predominant subtypes changed with treatment and progression. The luminal B, HER2, and basal subtypes exhibited shorter PFS in CDK4/6 inhibitor combinations when assessed in the pretreatment biopsies; however, they were not associated with OS. Using unbiased approaches, cell cycle-associated gene sets were strongly associated with shorter PFS in pretreatment biopsies irrespective of endocrine therapy. Estrogen receptor signaling gene sets were associated with longer PFS particularly in the AI-treated cohort. Together, these data suggest that there are distinct pathological and biological features of HR+/HER2- breast cancer associated with response to CDK4/6 inhibitors. Clinical trial registration number: NCT04526587.

Biomarkers in Breast Cancer: An Old Story with a New End

Breast cancer is the second most frequent cancer in the world. It is a heterogeneous disease and the leading cause of cancer mortality in women. Advances in molecular technologies allowed for the identification of new and more specifics biomarkers for breast cancer diagnosis, prognosis, and risk prediction, enabling personalized treatments, improving therapy, and preventing overtreatment, undertreatment, and incorrect treatment. Several breast cancer biomarkers have been identified and, along with traditional biomarkers, they can assist physicians throughout treatment plan and increase therapy success. Despite the need of more data to improve specificity and determine the real clinical utility of some biomarkers, others are already established and can be used as a guide to make treatment decisions. In this review, we summarize the available traditional, novel, and potential biomarkers while also including gene expression profiles, breast cancer single-cell and polyploid giant cancer cells. We hope to help physicians understand tumor specific characteristics and support decision-making in patient-personalized clinical management, consequently improving treatment outcome.

Transcriptomic Analysis of Breast Cancer Patients Sensitive and Resistant to Chemotherapy: Looking for Overall Survival and Drug Resistance Biomarkers

Worldwide breast cancer ranks first in mortality and incidence rates in women over 20 years old. Rather than one disease, breast cancer is a heterogeneous group of diseases that express distinct molecular profiles. Neoadjuvant chemotherapy is an important therapeutic strategy for breast cancer patients independently of their molecular subtype, with the drawback of resistance development. In addition, chemotherapy has adverse effects that combined with resistance could contribute to lower overall survival. Although great efforts have been made to find diagnostic and prognostic biomarkers for breast cancer and for response to targeted and immune therapy for this pathology, little has been explored regarding biomarkers of response to anthracyclines and taxanes based neoadjuvant chemotherapy. This work aimed to evaluate the molecular profile of patients who received neoadjuvant chemotherapy to identify differentially expressed genes (DEGs) that could be used as biomarkers of chemotherapy response and overall survival. Breast cancer patients who were candidates for neoadjuvant chemotherapy were enrolled in this study. After treatment and according to their pathological response, they were assigned as sensitive or resistant. To evaluate DEGs, Gene Ontology, Kyoto Encyclopedia Gene and Genome (KEGG), and protein–protein interactions, RNA-seq information from all patients was obtained by next-generation sequencing. A total of 1985 DEGs were found, and KEGG analysis indicated a great number of DEGs in metabolic pathways, pathways in cancer, cytokine–cytokine receptor interactions, and neuroactive ligand-receptor interactions. A selection of 73 DEGs was used further for an analysis of overall survival using the METABRIC study and the ductal carcinoma dataset of The Cancer Genome Atlas (TCGA) database. Nine DEGs correlated with overall survival, of which the subexpression of C1QTNF3, CTF1, OLFML3, PLA2R1, PODN, KRT15, HLA-A, and the overexpression of TUBB and TCP1 were found in resistant patients and related to patients with lower overall survival.

OUP accepted manuscript

Background

A study was initiated at Roswell Park Comprehensive Cancer Center to capture the real-world experience related to the use of CDK4/6 inhibitors (Ciclibs) for the treatment of metastatic hormone receptor-positive and HER2-negative breast cancer (HR+/HER2-).

Patients and Methods

A total of 222 patients were evaluated who received CDK4/6 inhibitors in the period from 2015 to 2021. Detailed clinical and demographic information was obtained on each patient and used to define clinical and demographic features associated with progression-free survival on CDK4/6 inhibitor-based therapies.

Results

In this real-world analysis, the majority of patients received palbociclib as the CDK4/6 inhibitor with letrozole or fulvestrant as the predominant endocrine therapies. The median progression-free survival (PFS) in the letrozole (27.6 months) and fulvestrant (17.2 months) groups were comparable to that observed in clinical trials. As expected, age at start of the treatment and menopausal status influenced endocrine therapy utilization but were not associated with PFS. Patients with recurrent disease had shorter PFS (P = .0024) than those presenting with de novo metastasis. The presence of visceral metastasis trended toward shorter PFS (P = .051). Similarly, prior endocrine therapy (P = .003) or chemotherapy (P = .036) was associated with shorter PFS. Body mass index was not associated with PFS or with dose interruption and/or modification. While the number of minorities in this analysis is limited (n = 26), these patients as a group had statistically shorter PFS on treatment (P = .002).

Conclusions

The real-world progression-free survival with CDK4/6 inhibitors mimics that observed in the clinical trial. A number of clinical and demographic features were associated with PFS on CDK4/6 inhibitor-based therapy. Further studies are ongoing to validate these findings incorporating additional cancer centers.

The impact of Oncotype DX testing on adjuvant chemotherapy decision making in 1-3 node positive breast cancer

BACKGROUND

Oncotype DX testing has reduced the use of adjuvant chemotherapy in node-negative early breast cancer but less is known about its impact in node positive patients.

AIM

This study aimed to investigate the impact of Oncotype DX gene assay testing on the decision to offer adjuvant chemotherapy in oestrogen positive, human epidermal growth factor receptor 2 negative, 1-3 lymph node positive patients.

METHODS

Retrospective review of all node positive patients who underwent Oncotype DX testing at a single centre. Clinicopathological data, as well as estimated survival benefit data (from the PREDICT tool), was evaluated by a multidisciplinary group of surgeons and oncologists. Treatment decisions based on clinicopathological data were compared to recurrence scores (RS). A cut off RS > 30 was used to offer adjuvant chemotherapy.

RESULTS

The 69 patients were identified, of which 9 (13%) had an RS > 30 and assigned a high-genomic risk of recurrence. The 32 patients (46.4%) were offered adjuvant chemotherapy. Overall based on the use of the RS, the decision to offer adjuvant chemotherapy changed in 36% of patients, and ultimately 24 patients (34.7%) would have been spared chemotherapy.

CONCLUSION

Using clinicopathological data alone to make decisions regarding adjuvant chemotherapy in node positive breast cancer leads to overtreatment. Additional information on tumour biology as assessed by the Oncotype DX RS helps to select those patients who will benefit from adjuvant chemotherapy and spare patients from unnecessary chemotherapy.

Discordance in Oncotype DX Breast Recurrence Score® Results for Bilateral Breast Cancer

BACKGROUND

The Oncotype DX Breast Recurrence Score^® assay is a clinically useful tool to determine the benefit of chemotherapy in the treatment of early-stage, hormone-receptor-positive breast cancer. Bilateral breast cancer (BBC) is found in ~ 5% of patients with breast cancer, and data regarding discordance of Oncotype DX results between BBC defined by current TAILORx subgroups are limited. Our goals are to study the rate of Oncotype DX discordance between BBC and investigate whether such differences can affect chemotherapy treatment discussions.

METHODS

Patients with BBC were identified in US samples submitted to Genomic Health for 21-gene testing between January 2019 and July 2020. The risk categories were defined as 0-25 and 26-100 as well as 0-17, 18-30, and 31-100 for all patients. Subgroup analysis was also performed for node-negative women age ≤ 50 years with Recurrence Score results of 0-15, 16-20, 21-25, and 26-100.

RESULTS

944 BBC patients with known nodal status (702 node negative, 242 node positive) were identified and included. Among node-negative patients aged > 50 years, the rate of discordance in Recurrence Score by group (0-25 and 26-100) was 4.2% (n = 598). For node-negative patients aged ≤ 50 years, the risk group was discordant in < 3% when considering the risk grouping of 0-25 and 26-100. However, upon subgroup analysis based on TAILORx analysis, the rate of discordance was 48.1% in these younger patients (n = 104).

CONCLUSIONS

This study shows that a clinically relevant rate of discordance in Oncotype DX results in patients with BBC may impact medical decision-making regarding chemotherapy.

Patients' and Oncologists' Knowledge and Expectations Regarding Tumor Multigene Next-Generation Sequencing: A Narrative Review

BACKGROUND

Tumor multigene next-generation sequencing (NGS) is increasingly being offered to cancer patients to guide clinical management and determine eligibility for clinical trials. We undertook a review of studies examining the knowledge and attitudes of patients and oncologists regarding the primary results and potential secondary findings of such testing.

MATERIALS AND METHODS

A search was conducted through the MEDLINE database using the following keywords: "neoplasms" and "molecular sequencing / genome sequencing / tumor profiling / NGS / whole exome sequencing" and "patient / oncologist" and "knowledge / attitudes / satisfaction / experience / evaluation / perspective / practice / preference." Articles meeting the inclusion criteria and additional relevant articles from their references were selected.

RESULTS

From 1,142 publications identified by the search and 9 from references, 21 publications were included in the final review. Patients generally had positive attitudes toward tumor NGS despite relatively little knowledge of test-related genetics concepts, but their expectations often exceeded the reality of low clinical utility. Patients with higher education and greater genetics knowledge had more realistic expectations and a more altruistic view of the role of NGS. Attitudes toward disclosure of secondary findings were highly variable. Oncologists had poor to moderate genomic literacy; they communicated challenges with tempering patient expectations and deciding what information to disclose.

CONCLUSION

Patients considering undergoing tumor NGS should be provided with easily understandable resources explaining the procedure, goals, and probable outcomes, whenever possible based on evidence-based guidelines. Continuing medical education programs on this topic for oncology health care professionals should strive to improve their genomic literacy and instruct them on how to optimally present this information to their patients.

IMPLICATIONS FOR PRACTICE

Oncologists are increasingly offering tumor multigene testing to patients with advanced cancers to guide more "personalized" treatment and/or determine eligibility for clinical trials. However, patients often have inadequate understanding and unrealistic expectations. Oncologists must ensure that they themselves have sufficient knowledge of the benefits and limitations of testing and must provide their patients with appropriate educational resources. Prior to testing, patients should be told the likelihood of finding a mutation in their specific tumor type for which a targeted treatment or clinical trial is available. Patients also need clear information about the possibility and implications of secondary findings.

Factors associated with chemotherapy benefit in breast cancer patients with midrange Oncotype DX breast recurrence scores

Chemotherapy for patients with hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, node-negative breast cancer, and with midrange Oncotype DX breast recurrence scores (RS) still needs to be further individualized. To improve the treatment decision making, we aimed to develop a method that provides a single score based on multiple factors associated with chemotherapy benefit. We analyzed Surveillance, Epidemiology, and End Results registry data from 31,731 patients with hormone receptor-positive, HER2-negative, node-negative breast cancer and midrange RS characterized by sociodemographic (age and marital status) and clinicopathologic (tumor size, histologic grade, progesterone receptor status, broad histological classification, lesion laterality, and lesion overlap) features and stratified by RS ranges. For the entire sample and for each characteristic, overall survival was compared between patients who underwent chemotherapy and those who did not (or status unknown) within each RS stratum. There was no any association between chemotherapy and survival for patients with RS = 11-15. However, for patients with RS = 16-25, a chemotherapy benefit was associated with tumor size, histologic grade, progesterone receptor status, histological type, and lesion laterality. In addition, overlapping lesion of breast and married at diagnosis might provide additional predictive information of chemotherapy benefit when RS = 21-25. A simple and effective algorithm was designed by combining these factors to output a novel and personalized chemotherapy benefit score to effectively identify patients with RS = 16-25 who would most likely benefit from chemotherapy, which might facilitate improved treatment by providing individualized recommendations.

Overview of Breast Cancer and Implications of Overtreatment of Early-Stage Breast Cancer: An Indian Perspective

The prevalence and mortality of breast cancer is increasing in Asian countries, including India. With advances in medical technology leading to better detection and characterization of the disease, it has been possible to classify breast cancer into various subtypes using markers, which helps predict the risk of distant recurrence, response to therapy, and prognosis using a combination of molecular and clinical parameters. Breast cancer and its therapy, mainly surgery, systemic therapy (anticancer chemotherapy, hormonal therapy, targeted therapy, and immunotherapy), and radiation therapy, are associated with significant adverse influences on physical and mental health, quality of life, and the economic status of the patient and her family. The fear of recurrence and its devastating effects often leads to overtreatment, with a toxic cost to the patient financially and physically in cases in which this is not required. This article discusses some aspects of a breast cancer diagnosis and its impact on the various facets of the life of the patient and her family. It further elucidates the role of prognostic factors, the currently available biomarkers and prognostic signatures, and the importance of ethnically validating biomarkers and prognostic signatures.

Spotlight on the utility of the Oncotype DX® breast cancer assay

The Oncotype DX^® assay was developed to address the need for optimizing the selection of adjuvant systemic therapy for patients with estrogen receptor (ER)-positive, lymph node-negative breast cancer. It has ushered in the era of genomic-based personalized cancer care for ER-positive primary breast cancer and is now widely utilized in various parts of the world. Together with several other genomic assays, Oncotype DX has been incorporated into clinical practice guidelines on biomarker use to guide treatment decisions. The Oncotype DX result is presented as the recurrence score which is a continuous score that predicts the risk of distant disease recurrence. The assay, which provides information on clinicopathological factors, has been validated for use in the prognostication and prediction of degree of adjuvant chemotherapy benefit in both lymph node-positive and lymph node-negative early breast cancers. Clinical studies have consistently shown that the Oncotype DX has a significant impact on decision making in adjuvant therapy recommendations and appears to be cost-effective in diverse health care settings. In this article, we provide an overview of the validation and clinical impact studies for the Oncotype DX assay. We also discuss its potential use in the neoadjuvant setting, as well as the more recent prospective validation trials, and the economic and utility implications of studies that use a lower cutoff score to define low-risk disease.

Does lymph node status influence adjuvant therapy decision-making in women 70 years of age or older with clinically node negative hormone receptor positive breast cancer?

BACKGROUND

Women ≥70 years old with clinically (c) lymph node (LN) negative (-), hormone receptor (HR) positive (+) breast cancer are recommended not to be routinely staged with a sentinel LN biopsy. We sought to determine how this affects adjuvant decision-making.

METHODS

Statistical analyses were performed to determine the association of LN evaluation with adjuvant chemotherapy and radiation therapy in cLN-, HR + breast cancer patients in the National Cancer Database.

RESULTS

Between 2004 and 2013, there were 193,728 patients aged 70-90 with cLN-, HR + breast cancer; 15.0% were LN+. LN + patients were more likely to receive chemotherapy (28.3% vs. 5.5%, p < 0.001), hormonal therapy (83.6% vs. 71.4%, p < 0.001), post-lumpectomy radiation therapy (81.4% vs. 73.6%, p < 0.001) and post-mastectomy radiation therapy (30.3% vs. 5.1%, p < 0.001).

CONCLUSION

15% of patients aged 70-90 will be LN+. These patients more frequently receive systemic and radiation therapy. LN status may affect treatment in these patients.

High-grade poorly differentiated neuroendocrine carcinoma of the breast with low oncotype Dx recurrence score: A case report

Primary neuroendocrine carcinoma of the breast (NECB) is a rare malignant tumor with controversial biological behavior and a lack of data guiding treatment decisions due to its scarcity. Cancer gene-expression profiling tests provide a better indication of clinical prognosis and help determine the best clinical management versus the traditional clinical and pathological parameters. This is a report of a NECB with a genetic assay that showed a low-risk tumor despite high-grade and poorly differentiated histopathological features. Patient outcomes correlate with the low risk classification without the need for adjuvant chemotherapy despite the standard clinical-pathologic approach. Analysis of cancer related genes expression and outcomes in historical NECB may elucidate new insight of this rare disease.

Adjuvant endocrine therapy alone in patients with node-positive, luminal A type breast cancer

Luminal A breast cancer has a much better prognosis than other subtypes, with a low risk of local or regional recurrence. However, there is controversy around under- versus overtreatment with regard to adjuvant treatment of node-positive, luminal A breast cancer. The purpose of this study was to identify whether adjuvant systemic chemotherapy has any benefit in node-positive, luminal A breast cancer and to evaluate feasibility of endocrine therapy without chemotherapy in this group.This was a retrospective study of 11,025 patients who were surgically treated for invasive breast cancer at Samsung Medical Center between January 2004 and December 2013. Luminal A subtype was defined as ER+, HER2-, and Ki-67 < 14%. We compared AC based (AC: doxorubicin or epirubicin, plus cyclophosphamide) adjuvant chemotherapy versus endocrine therapy without chemotherapy in patients with node-positive, luminal A breast cancer.We performed 1: n matching, with a maximum n of 8 on endocrine therapy group (n = 50) to chemotherapy group (n = 642). The median age of the patients in each group at the time of surgery was 58.3 ± 9.5 years in the chemotherapy group and 58.7 ± 11.7 in the endocrine therapy only group. The median follow-up time was 51.9 months (range, 1-125 months). In multivariable analysis, omission of adjuvant chemotherapy in luminal A cancer had no influence on OS and DFS. Axillary lymph node metastasis and progesterone receptor (PR) status were significantly different between the endocrine therapy alone group and the chemotherapy group in terms of OS. Nuclear grade, PR status, and adjuvant radiotherapy were significantly different between the endocrine therapy alone group and the chemotherapy group with regard to DFS. In survival analysis, there were no differences in OS (P = .137) and DFS (P = .225) between the 2 groups.Adjuvant chemotherapy could provide little benefit to postmenopausal patients with luminal A, node-positive breast cancer, and endocrine therapy alone may help reduce morbidity. Future studies with a large number of patients and longer follow-up time are necessary to determine whether chemotherapy might be avoided in this patient population.

[Validation and clinical application of MammaPrint® in patients with breast cancer]

BACKGROUND

In recent years, advances in molecular biology have resulted in innovations in breast cancer diagnostics and therapeutics. The development of genomics has revolutionized our understanding of this disease. MammaPrint^® was developed as a diagnostic tool to predict risk of breast cancer recurrence using the expression of 70 genes altering the clinicopathologic paradigm of selection of patients for adjuvant cytotoxic chemotherapy.

MATERIALS AND METHODS

A study of stage i-ii breast cancer patients on whom the MammaPrint^® genomic assay was performed.

RESULTS

The use of the MammaPrint^® assay was a decisive factor for the recommendation of adjuvant treatment with chemotherapy and/or hormone therapy in patients with high risk for relapse. In our group, the patients with low-risk have not presented local or systemic recurrences DISCUSSION: The determination of the genetic characteristics and its alterations in breast cancer, is fundamentally important for a better identification of risk, as well as a better selection of cancer therapy.

CONCLUSION

MammaPrint^® is an effective study to determine risk of recurrence of in early stage breast cancer.

Defining the transcriptional and biological response to CDK4/6 inhibition in relation to ER+/HER2- breast cancer

ER positive (ER+) and HER2 negative (HER2-) breast cancers are routinely treated based on estrogen dependence. CDK4/6 inhibitors in combination with endocrine therapy have significantly improved the progression-free survival of patients with ER+/HER2- metastatic breast cancer. Gene expression profiling in ER+/HER2- models was used to define the basis for the efficacy of CDK4/6 inhibitors and develop a gene expression signature of CDK4/6 inhibition. CDK4/6 inhibition robustly suppressed cell cycle progression of ER+/HER2- models and complements the activity of limiting estrogen. Chronic treatment with CDK4/6 inhibitors results in the consistent suppression of genes involved in cell cycle, while eliciting the induction of a comparable number of genes involved in multiple processes. The CDK4/6 inhibitor treatment shifted ER+/HER2- models from a high risk (luminal B) to a low risk (luminal A) molecular-phenotype using established gene expression panels. Consonantly, genes repressed by CDK4/6 inhibition are strongly associated with clinical prognosis in ER+/HER2- cases. This gene repression program was conserved in an aggressive triple negative breast cancer xenograft, indicating that this is a common feature of CDK4/6 inhibition. Interestingly, the genes upregulated as a consequence of CDK4/6 inhibition were more variable, but associated with improved outcome in ER+/HER2- clinical cases, indicating dual and heretofore unknown consequence of CDK4/6 inhibition. Interestingly, CDK4/6 inhibition was also associated with the induction of a collection of genes associated with cell growth; but unlike suppression of cell cycle genes this signaling was antagonized by endocrine therapy. Consistent with the stimulation of a mitogenic pathway, cell size and metabolism were induced with CDK4/6 inhibition but ameliorated with endocrine therapy. Together, the data herein support the basis for profound interaction between CDK4/6 inhibitors and endocrine therapy by cooperating for the suppression of cell cycle progression and limiting compensatory pro-growth processes that could contribute to therapeutic failure.

Recognizing the Limitations of Cancer Overdiagnosis Studies: A First Step Towards Overcoming Them

Numerous studies have attempted to quantify the number of breast cancers that would never have been diagnosed in the absence of screening. Unfortunately, results are highly variable across studies and there is considerable disagreement about both the frequency of overdiagnosis and the validity of different methodologic approaches. In this Commentary, we review limitations of the two major approaches used in existing studies. Studies that use excess incidence as a proxy for overdiagnosis require a valid estimate of incidence in the absence of screening and sufficient follow-up to ensure the excess excludes relevant (ie, nonoverdiagnosed) cancers detected early. The requirement of sufficient follow-up applies to both population studies and clinical trials, but only certain clinical trial designs have the potential to yield unbiased results. Studies that model disease natural history to infer overdiagnosis must, in addition, examine whether their models produce valid estimates in the presence of nonprogressive cases. In this setting, limited follow-up could lead to a lack of identifiability of the parameters needed to accurately infer overdiagnosis. In a polarized research community, the excess incidence and modeling approaches are generally viewed as competitors, but we argue that they are complementary, with models being more complex but having greater potential to inform about disease natural history and the outcomes of candidate screening policies. Rather than arguing why one approach should be preferred to another, investigators should focus on developing studies that generate reliable estimates of overdiagnosis. Recognizing that both approaches have limitations, which existing studies rarely overcome, is a first step towards reconciling methodologic perspectives and achieving consensus about the real magnitude of the overdiagnosis problem.

The Effect of Treatment Advances on the Mortality Results of Breast Cancer Screening Trials: A Microsimulation Model

BACKGROUND

Mammography trials, which are the primary sources of evidence for screening benefit, were conducted decades ago. Whether advances in systemic therapies have rendered previously observed benefits of screening less significant is unknown.

OBJECTIVE

To compare the outcomes of breast cancer screening trials had they been conducted using contemporary systemic treatments with outcomes of trials conducted with previously used treatments.

DESIGN

Computer simulation model of 3 virtual screening trials with similar reductions in advanced-stage cancer cases but reflecting treatment patterns in 1975 (prechemotherapy era), 1999, or 2015 (treatment according to receptor status).

DATA SOURCES

Meta-analyses of screening and treatment trials; study of dissemination of primary systemic treatments; SEER (Surveillance, Epidemiology, and End Results) registry.

TARGET POPULATION

U.S. women aged 50 to 74 years.

TIME HORIZON

10 and 25 years.

PERSPECTIVE

Population.

INTERVENTION

Mammography, chemotherapy, tamoxifen, aromatase inhibitors, and trastuzumab.

OUTCOME MEASURES

Breast cancer mortality rate ratio (MRR) and absolute risk reduction (ARR) obtained by the difference in cumulative breast cancer mortality between control and screening groups.

RESULTS OF BASE-CASE ANALYSIS

At 10 years, screening in a 1975 trial yielded an MRR of 90% and an ARR of 5 deaths per 10,000 women. A 2015 screening trial yielded a 10-year MRR of 90% and an ARR of 3 deaths per 10,000 women.

RESULTS OF SENSITIVITY ANALYSIS

Greater reductions in advanced-stage disease yielded a greater screening effect, but MRRs remained similar across trials. However, ARRs were consistently lower under contemporary treatments. When contemporary treatments were available only for early-stage cases, the MRR was 88%.

LIMITATION

Disease models simplify reality and cannot capture all breast cancer subtypes.

CONCLUSION

Advances in systemic therapies for breast cancer have not substantively reduced the relative benefits of screening but have likely reduced the absolute benefits because of their positive effect on breast cancer survival.

PRIMARY FUNDING SOURCE

University of Washington and National Cancer Institute.

Correlative Analysis of miRNA Expression and Oncotype Dx Recurrence Score in Estrogen Receptor Positive Breast Carcinomas

Altered expression of miRNAs has been observed in many types of cancer, including breast cancer, and shown to contribute to cancer growth, aggressiveness, and response to therapies. In this pilot study, we investigated the possible correlation of miRNAs with risk of recurrence of estrogen receptor positive, lymph node-negative mammary carcinomas as determined by the Oncotype DX® Breast Cancer assay. To accomplish this, we extracted RNA from a collection of breast carcinomas that had previously been analyzed by Oncotype DX®. Multiple Let-7 family members were negatively correlated with the recurrence score (RS), which is consistent with their tumor suppressor properties. Additional miRNAs were found to positively correlate with RS, including miR-377-5p, miR-633b, miR-548t and miR-3648. Pathway analysis of putative and validated targets suggests that these miRNAs may have a diverse range of functions that may contribute to tumor recurrence. Taken together, these findings provide evidence that a miRNA expression signature can be developed to aid existing methods to determine the risk of recurrence for women with estrogen receptor positive breast cancers treated with endocrine therapy.

Adjuvant chemotherapy: which patient? What regimen?

In the past, treatment decisions regarding adjuvant chemotherapy in early breast cancer (EBC) were made solely based on clinicopathologic factors. However, with increased awareness of the importance of underlying tumor biology, we are now able to use genomic analyses to determine molecular breast cancer subtype and thus identify patients with tumors that are chemotherapy resistant and unlikely to benefit from the addition of chemotherapy. Although genomics has allowed some patients to avoid chemotherapy-specifically those with luminal A-like breast cancer-these assays do not indicate which regimen is most appropriate. For this, consideration must be given to the combination of underlying tumor biology, tumor stage, and patient characteristics, such as age and tolerability of side effects.

The Role of MicroRNAs as Predictors of Response to Tamoxifen Treatment in Breast Cancer Patients

Endocrine therapy is a key treatment strategy to control or eradicate hormone-responsive breast cancer. However, resistance to endocrine therapy leads to breast cancer relapse. The recent extension of adjuvant tamoxifen treatment up to 10 years actualizes the need for identifying biological markers that may be used to monitor predictors of treatment response. MicroRNAs are promising biomarkers that may fill the gap between preclinical knowledge and clinical observations regarding endocrine resistance. MicroRNAs regulate gene expression by posttranscriptional repression or degradation of mRNA, most often leading to gene silencing. MicroRNAs have been identified directly in the primary tumor, but also in the circulation of breast cancer patients. The few available studies investigating microRNA in patients suggest that seven microRNAs (miR-10a, miR-26, miR-30c, miR-126a, miR-210, miR-342 and miR-519a) play a role in tamoxifen resistance. Ingenuity Pathway Analysis (IPA) reveals that these seven microRNAs interact more readily with estrogen receptor (ER)-independent pathways than ER-related signaling pathways. Some of these pathways are targetable (e.g., PIK3CA), suggesting that microRNAs as biomarkers of endocrine resistance may have clinical value. Validation of the role of these candidate microRNAs in large prospective studies is warranted.

Oncotype DX in Bilateral Synchronous Primary Invasive Breast Cancer

BACKGROUND

Synchronous bilateral breast cancers frequently share the same estrogen receptor (ER) status, yet may differ in other histopathologic features. We sought to examine concordance rates of Oncotype DX recurrence score (RS) testing in women with synchronous bilateral ER-positive breast cancer.

METHODS

Institutional databases were reviewed to identify patients with synchronous (within 6 months) bilateral primary invasive breast cancer and multiple RSs. RSs were stratified by risk group (RS < 18, low; RS 18-30, intermediate; RS ≥ 31, high) and considered discordant if they reflected different risk groups.

RESULTS

From 2005-2014, a total of 115 patients presented with synchronous bilateral invasive breast cancer; 43 (37 %) had two RSs available. Median patient age was 60 years (42-84), median tumor size was 1.2 cm (0.5-3.7), and all cases were HER2 negative and node negative. Of 86 RSs, 63 (73 %) were low risk, 20 (23 %) were intermediate risk, and 3 (3 %) were high risk. RSs were concordant in 29 (67 %) patients. Patients with concordant RSs were older (62 years vs. 56 years) and had median levels of progesterone receptor (PR) expression that were higher and more similar-80 and 85 % for bilateral cancers, respectively, compared with 55 and 75 % for bilateral cancers in discordant cases. Discordant RS led to a treatment change in 8/14 (57 %) cases.

CONCLUSIONS

Among women with synchronous bilateral ER-positive HER2-negative breast cancer, RSs were concordant in 67 % of cases. Concordance rates may be higher in older women or among those with comparable levels of PR expression. These data suggest that testing of both tumors should be considered in patients who are candidates for adjuvant chemotherapy.

Application of a 70-Gene Expression Profile to Japanese Breast Cancer Patients

BACKGROUND

As data on using MammaPrint®, a 70-gene expression profile for molecular subtyping of breast cancer, are limited in Japanese patients, we aimed to determine the gene profiles of Japanese patients using MammaPrint and to investigate its possible clinical application for selecting adjuvant treatments.

PATIENTS AND METHODS

50 women treated surgically at our institution were examined. The MammaPrint results were compared with the St Gallen 2007 and intrinsic subtype risk categorizations.

RESULTS

Of 38 cases judged to be at intermediate risk based on the St Gallen 2007 Consensus, 11 (29%) were in the high-risk group based on MammaPrint. 1 of the 30 luminal A-like tumors (3%) was judged as high risk based on MammaPrint results, whereas 7 of the 20 tumors (35%) categorized as luminal B-like or triple negative were in the low-risk group. There have been no recurrences to date in the MammaPrint group, and this is possibly attributable to most of the high-risk patients receiving chemotherapy that had been recommended on the basis of their MammaPrint results.

CONCLUSIONS

Our results indicate that MammaPrint is applicable to Japanese patients and that it is of potential value in current clinical practice for devising individualized treatments.

Use and Costs for Tumor Gene Expression Profiling Panels in the Management of Breast Cancer From 2006 to 2012: Implications for Genomic Test Adoption Among Private Payers

Gene expression profiling has diffused into clinical practice. Reimbursements by insurers have increased, and average out-of-pocket costs to patients have decreased, seemingly driven by improved coverage for testing over time.

Computational prognostic indicators for breast cancer

Breast cancer remains the leading cause of cancer-related mortality in women. Comprehensive genomics, proteomics, and metabolomics studies are emerging that offer an opportunity to model disease biology, prognosis, and response to specific therapies. Although many biomarkers have been identified through advances in data mining techniques, few have been applied broadly to make patient-specific decisions. Here, we review a selection of breast cancer prognostic indicators and their implications. Our goal is to provide clinicians with a general evaluation of emerging computational methodologies for outcome prediction.

Evaluation of the ability of adjuvant tamoxifen-benefit gene signatures to predict outcome of hormone-naive estrogen receptor-positive breast cancer patients treated with tamoxifen in the advanced setting

To identify molecular markers indicative of response to tamoxifen and easily implemented in the routine setting, we recently reported three gene signatures that could stratify post-menopausal tamoxifen-treated, estrogen receptor-positive (ER+) patients according to outcome in the adjuvant setting. Here, we evaluated the predictive potential of the total of 14 genes included in the 3 gene signatures using 2 hormone-naïve Dutch ER+ cohorts of a total of 285 recurrent breast cancer patients treated with first-line tamoxifen. mRNA levels were measured by reverse transcriptase quantitative PCR (RT-qPCR) and the length of progression-free survival (PFS) was used as the primary endpoint. A Mann-Whitney U test was used to select for differentially expressed genes between tumors of patients who showed or did not show progressive disease within 6 months after start of tamoxifen treatment. Cox univariate and multivariate regression analysis for PFS were used to further assess their (independent) predictive potential. Five (BCAR3, BCL2, ESR1, IGF1R, and NCOA1) of the 14 genes analyzed showed significantly higher mRNA levels in tumors of patients who showed no disease progression within 6 months. Only BCAR3, BCL2 and NAT1 were significantly associated with a favorable PFS in multivariate analysis that included the traditional predictive factors: age, dominant relapse site, disease-free interval, ER and progesterone receptor (PGR), and adjuvant chemotherapy. This study shows that BCAR3, BCL2 and NAT1 in particular exhibit predictive promise regarding the efficacy of tamoxifen treatment in recurrent disease, in addition to the previously shown favorable outcome in the adjuvant setting.

The multigene signature MammaPrint impacts on multidisciplinary team decisions in ER+, HER2- early breast cancer

Background:

Validated multigene signatures (MGS) provide additional prognostic information when evaluating clinical features of ER⁺, HER2⁻ early breast cancer. We have studied the quantitative and qualitative impact of MGS on multidisciplinary team (MDT) recommendations.

Methods:

We prospectively recruited 75 ER⁺, HER2⁻ breast cancer patients. Inclusion was based on biopsy assessment of grade, hormone receptor status, HER2, clinical tumour and nodal status. A fresh tissue sample was sent for MammaPrint (MP), TargetPrint analysis at surgery. Clinical risk was decided by the MDT in the absence of MP results and repeated following the collection of MP results. Decision changes were recorded and a health technology assessment was undertaken to compare cost effectiveness.

Results:

The majority of patients were assigned low to intermediate clinical risk by the MDT. According to MP, 76% were low risk. A very high correlation between local IHC and the TargetPrint assessment was shown. In over a third of patients, discordance between clinical and molecular risk was observed. Decision changes were recorded in half of these cases (18.6%) and resulted in two out of three patients not requiring chemotherapy. The use of MP was also found to be more cost effective.

Conclusions:

The multigene signature MP revealed clinical and molecular risk discordance in a third of patients. The impact of this on MDT recommendations was most profound in cases where few clinical risk factors were observed and enabled some women to forgo chemotherapy. The use of MGS is unlikely to have an impact in either clinically low-risk women or in patients with more than one relative indication for chemotherapy.

The continued evidence from overviews: what is the clinical utility?

The Oxford Overview process has provided us with extremely high-powered meta-analyses assessing the role of adjuvant chemotherapy in early breast cancer. From the most recent publication, the proportional benefits from chemotherapy are relatively equivalent across all patient subgroups, a finding contradictory to our growing understanding of the role of tumour biology in dictating chemosensitivity. Several factors, including heterogeneity of patient groups and chemotherapy regimens, lack of data on underlying tumour biological subtypes, and confounding effect of chemotherapy-induced ovarian suppression in premenopausal women with hormone receptor positive breast cancer, impact on the applicability and clinical utility of the Overview in current and future oncological practice. With these considerations, the Overview has become less clinically relevant as a tool for guiding adjuvant chemotherapy treatment decisions, and a new direction is required.

Prognostic and predictive markers for personalized adjuvant therapy for non-small-cell lung cancer patients

Adjuvant chemotherapy following surgical resection in non-small-cell lung cancer patients with large tumors (>4 cm) or tumors with lymph node metastases has emerged as a standard of care. The benefits of adjuvant chemotherapy are modest, with a 5-year survival improvement of only 5–10%. In addition, survival rates of 25% or greater with surgery alone suggest that some patients do not need adjuvant therapy. Therefore, there is a need to develop prognostic and predictive markers to identify patients in need of adjuvant therapy and the patients likely to benefit from such therapy. Many factors have been evaluated for this purpose and some of these factors, such as visceral pleural invasion, can influence the decision to use adjuvant chemotherapy. However, most of the available data are retrospective, which limits the utility of these markers in current practice. Ongoing trials are evaluating many promising markers and may guide adjuvant therapy in the future.

The impact of the Oncotype Dx breast cancer assay in clinical practice: a systematic review and meta-analysis

The impact of the Oncotype Dx (ODX) breast cancer assay on adjuvant chemotherapy (ACT) treatment decisions has been evaluated in many previous studies. However, it can be difficult to interpret the collective findings, which were conducted in diverse settings with limited sample sizes. We conducted a systematic review and meta-analysis to synthesize the results and provide insights about ODX utility. Studies, identified from PubMed, Embase, ASCO, and SABCS, were included if patients had ER+, node -, early-stage breast cancer, reported use of ODX to inform actual ACT decisions. Information was summarized and pooled according to: (1) distribution of ODX recurrence scores (RS), (2) impact of ODX on ACT recommendations, (3) impact of ODX on ACT use, and (4) proportion of patients following the treatment suggested by the ODX RS. A total of 23 studies met inclusion criteria. The distribution of RS categories was 48.8 % low, 39.0 % intermediate, and 12.2 % high (21 studies, 4,156 patients). ODX changed the clinical-pathological ACT recommendation in 33.4 % of patients (8 studies, 1,437 patients). In patients receiving ODX, receipt of ACT were: 28.2 % overall, 5.8 % low, 37.4 % intermediate, and 83.4 % high. Low RS patients were significantly more likely to follow the treatment suggested by ODX versus high RS patients RR: 1.07 (1.01–1.14) [corrected].The pooled results are consistent with most individual studies to date. The increased proportion of intermediate scores relative to original estimates may have implications for the clinical utility and cost impacts of testing. In addition, low versus high RS patients were significantly more likely to follow the ODX results, suggesting a tendency toward less aggressive treatment, despite a high ODX RS. Finally, there was a lack of studies on the impact of ODX on ACT use versus standard approaches, suggesting that additional studies are warranted.

C4.4A highly expressed in HER2-positive human breast cancers may indicate a good prognosis

BACKGROUND

The aim of our study was to investigate the association of C4.4A expression in breast tumors with both patients' clinicopathological characteristics and outcomes in order to clarify the significance of C4.4A in breast cancer.

METHODS

Primary breast cancer patients (n = 125, stage I-III) who had undergone breast mastectomy or breast-conserving surgery at our hospital between 2005 and 2011 were recruited for this study. Tumor samples were obtained from surgical specimens and expression status of C4.4A, estrogen receptors, progesterone receptors, human epidermal growth factor receptor 2 (HER2) and Ki67 was analyzed immunohistochemically, while HER2 amplification was examined using fluorescence in situ hybridization.

RESULTS

Multivariate analysis showed that HER2 positivity was the only independent predictive factor for C4.4A expression (odds ratio 5.31, 95 % confidence interval 2.04-15.72; P < 0.001). Univariate prognostic analysis of the relationship between C4.4A and disease-free survival showed that survival of patients with C4.4A-positive tumors was longer than that of patients with C4.4A-negative tumors in the HER2-positive subset (P = 0.004) while there was no significant difference in patient outcome according to C4.4A status for total patients (median observation period 37 months, range 1-92 months; P = 0.223).

CONCLUSIONS

We established a positive relationship between C4.4A and HER2 status, suggesting that C4.4A expression may be a prognostic factor for HER2-positive breast cancer patients.

The development and validation of a decision-analytic model representing the full disease course of acute myeloid leukemia

BACKGROUND

The treatment of acute myeloid leukemia (AML) is moving towards personalized medicine. However, due to the low incidence of AML, it is not always feasible to evaluate the cost-effectiveness of personalized medicine using clinical trials. Decision analytic models provide an alternative data source.

OBJECTIVE

The aim of this study was to develop and validate a decision analytic model that represents the full disease course of AML.

METHODS

We used a micro simulation with discrete event components to incorporate both patient and disease heterogeneity. Input parameters were calculated from patient-level data. Two hematologists critically evaluated the model to ensure face validity. Internal and external validity was tested by comparing complete remission (CR) rates and survival outcomes of the model with original data, other clinical trials and a population-based study.

RESULTS

No significant differences in patient and treatment characteristics, CR rate, 5-year overall and disease-free survival were found between the simulated and original data. External validation showed no significant differences in survival between simulated data and other clinical trials. However, differences existed between the simulated data and a population-based study.

CONCLUSIONS

The model developed in this study is proved to be valid for analysis of an AML population participating in a clinical trial. The generalizability of the model to a broader patient population has not been proven yet. Further research is needed to identify differences between the clinical trial population and other AML patients and to incorporate these differences in the model.

Identification and validation of a new set of five genes for prediction of risk in early breast cancer

Molecular tests predicting the outcome of breast cancer patients based on gene expression levels can be used to assist in making treatment decisions after consideration of conventional markers. In this study we identified a subset of 20 mRNA differentially regulated in breast cancer analyzing several publicly available array gene expression data using R/Bioconductor package. Using RTqPCR we evaluate 261 consecutive invasive breast cancer cases not selected for age, adjuvant treatment, nodal and estrogen receptor status from paraffin embedded sections. The biological samples dataset was split into a training (137 cases) and a validation set (124 cases). The gene signature was developed on the training set and a multivariate stepwise Cox analysis selected five genes independently associated with DFS: FGF18 (HR = 1.13, p = 0.05), BCL2 (HR = 0.57, p = 0.001), PRC1 (HR = 1.51, p = 0.001), MMP9 (HR = 1.11, p = 0.08), SERF1a (HR = 0.83, p = 0.007). These five genes were combined into a linear score (signature) weighted according to the coefficients of the Cox model, as: 0.125FGF18 − 0.560BCL2 + 0.409PRC1 + 0.104MMP9 − 0.188SERF1A (HR = 2.7, 95% CI = 1.9–4.0, p < 0.001). The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, intermediate or high risk of disease relapse as defined on the training set (p < 0.001). Our signature, after a further clinical validation, could be proposed as prognostic signature for disease free survival in breast cancer patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.

Comparison of EndoPredict and Oncotype DX test results in hormone receptor positive invasive breast cancer

Aim

Several multigene expression-based tests offering prognostic and predictive information in hormone-receptor positive early breast cancer were established during the last years. These tests provide prognostic information on distant recurrences and can serve as an aid in therapy decisions. We analyzed the recently validated reverse-transcription-quantitative-real-time PCR-based multigene-expression Endopredict (EP)-test on 34 hormone-receptor positive breast-cancer cases and compared the EP scores with the Oncotype DX Recurrence-scores (RS) obtained from the same cancer samples.

Methods

Formalin-fixed, paraffin-embedded invasive breast-cancer tissues from 34 patients were analyzed by the EP-test. Representative tumor blocks were analyzed with Oncotype DX prior to this study. Tumor tissue was removed from unstained slides, total-RNA was isolated and EP-analysis was performed blinded to Oncotype DX results.

Results

Extraction of sufficient amounts of RNA and generation of valid EP-scores were possible for all 34 samples. EP classified 11 patients as low-risk and 23 patients as high-risk. RS Score defined 15 patients as low-risk, 10 patients as intermediate-risk in and 9 patients as high-risk. Major-discrepancy occurred in 6 of 34 cases (18%): Low-risk RS was classified as high-risk by EP in 6 cases. Combining the RS intermediate-risk and high-risk groups to a common group, the concordance between both tests was 76%. Correlation between continuous EP and RS-scores was moderate (Pearson-coefficient: 0.65 (p<0.01).

Conclusion

We observed a significant but moderate concordance (76%) and moderate correlation (0.65) between RS and EP Score. Differences in results can be explained by different weighting of biological motives covered by the two tests. Further studies are needed to explore the clinical relevance of discrepant test results with respect of outcome.

Conveying genomic recurrence risk estimates to patients with early-stage breast cancer: oncologist perspectives

OBJECTIVE

The development and increased use of genomic profiling has led to refinement of breast cancer treatment. This study sought to examine medical and surgical oncologists' perceptions of factors related to the translation and integration of Oncotype DX® (Genomic Health, Inc., Redwood City, CA, USA) into routine clinical care.

METHODS

Twenty oncologists (10 medical and 10 surgical oncologists) participated in qualitative interviews. Questions centered on the following themes: oncologists' perceptions about the clinical utility of testing, the impact of patient preferences on the decision to test and use results to inform treatment decisions, methods of communicating risk associated with test results to patients, and benefits of and barriers to incorporating testing into multidisciplinary care settings.

RESULTS

Oncologists found Oncotype DX test results useful in their practice but had concerns as well. These included that some oncologists either used testing inappropriately or placed undue emphasis on the results at the expense of other clinical information. The use of intermediate test results, which have less clear clinical implications, incorporating results with patient treatment preferences, and the use of testing in multidisciplinary teams were noted as specific challenges.

CONCLUSION

Oncologists noted several benefits of testing and also many challenges, despite wide dissemination and common use. Education for health providers should include specific training in how to interpret and communicate the uncertainty inherent in genomic tests while integrating patient preferences to inform treatment decision making.

Targeting the PI3K/Akt/mTOR pathway for breast cancer therapy

Recent advances in genetics and genomics have revealed new pathways that are aberrantly activated in many breast cancers. Chief among these genetic changes are somatic mutations and/or gains and losses of key genes within the phosphoinositide 3-kinase (PI3K) pathway. Since breast cancer cell growth and progression is often dependent upon activation of the PI3K pathway, there has been intense research interest in finding therapeutic agents that can selectively inhibit one or more constituents of this signaling cascade. Here we review key molecules involved with aberrant PI3K pathway activation in breast cancers and current efforts to target these components for therapeutic gain.

Overview of personalized medicine in GI cancers

Cancer biomarkers may be used for prevention (identification of patients at high risk for cancer), estimating prognosis and/or repsonse to conventional chemotherapies, or guide the use of specific targeted therapies. This overview provides examples in each category for gastrointestinal cancers and reviews current concepts in personalized medicine.

Personalized therapy in breast cancer

Systemic treatment of non-metastatic breast cancer is based on endocrine therapy, cytotoxic chemotherapy, and molecular targeted therapy - with the major problems of immense overtreatment of patients who would not relapse without systemic therapy and the failure of treatment in others whose disease still recurs. These deficits can only be overcome by the identification of new and better prognostic and predictive markers. Currently, adjuvant treatment stratification is based on a limited number of established factors, namely locoregional tumour stage, age, grade, expression of hormone receptors, HER2, and Ki-67. Molecular profiling techniques, however, have revolutionized our understanding of breast cancer as a heterogeneous disease. Future results from even more comprehensive genetic analyses as part of the coordinated cancer genome projects will help to develop better treatment stratifications and new therapeutic approaches. Efforts to realize the dream of a personalized treatment for breast cancer will include drug development and intelligent design of trials for increasingly small subgroups of patients with specific host and disease characteristics. This will only be made possible by a strong cooperation between basic researchers and translational scientists, clinicians, as well as academia and industry.