Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features

Multidisciplinary care of patients with early-stage breast cancer

There is a compelling need for close coordination and integration of multiple specialties in the management of patients with early-stage breast cancer. Optimal patient care and outcomes depend on the sequential and often simultaneous participation and dialogue between specialists in imaging, pathologic and molecular diagnostic and prognostic stratification, and the therapeutic specialties of surgery, radiation oncology, and medical oncology. These are but a few of the various disciplines needed to provide modern, sophisticated management. The essential role for coordinated involvement of the entire health care team in optimal management of patients with early-stage breast cancer is likely to increase further.

Assessment of the Memorial Sloan-Kettering Cancer Center nomogram to predict sentinel lymph node metastases in a Dutch breast cancer population

AIM

Sentinel lymph node (SLN) biopsy is an accepted alternative to axillary lymph node dissection to assess the axillary tumour status in breast cancer patients. Memorial Sloan-Kettering Cancer Center (MSKCC) developed a nomogram to predict the likelihood of SLN metastases in breast cancer patients. Nomogram performance was tested on a Dutch population.

METHODS

Data of 770 breast cancer patients who underwent successful SLN biopsy were collected. SLN metastases were present in 222 patients. A receiver operating characteristic (ROC) curve was drawn and the area under the curve was calculated to assess the discriminative ability of the MSKCC nomogram. A calibration plot was drawn to compare actual versus nomogram-predicted probabilities.

RESULTS

The area under the ROC curve for the predictive nomogram was 0.67 (95% confidence interval 0.63-0.72) as compared to 0.75 in the original population. The nomogram was well-calibrated in the Dutch population.

CONCLUSIONS

In a Dutch population, the MSKCC nomogram estimated risk of sentinel node metastases in breast cancer patients well (i.e. calibration) with reasonable discrimination (area under ROC curve). Nomogram performance on core needle biopsy data has to be evaluated prospectively.

Molecular biology in breast cancer: should molecular classifiers be assessed by conventional tools or by gene expression arrays?

Breast cancer is a complex disease, with heterogeneous presentations and clinical courses. Standard clinico-pathological parameters, relying on single gene or protein characterization determined with sometimes poorly-reproducible technologies, have shown limitations in the classification of the disease and in the prediction of individual patient outcomes and responses to therapy. Gene-expression profiling has revealed great potential to accurately classify breast cancer and define patient prognosis and prediction to anti-cancer therapy. Nevertheless, the performance of molecular classifiers remains sub-optimal, and both technical and conceptual improvements are needed. It is likely that determining the ideal strategy for tailoring treatment of breast cancer will require a more systematic, structured and multi-dimensional approach than in the past. Besides implementing cutting-edge technologies to detect genetic and epigenetic cancer alterations, the future of breast cancer research will in all probability rely on the innovative and multilevel integration of molecular profiles with clinical parameters of the disease and patient-related factors.

Molecular Classification of Breast Cancer

This article reviews the conceptual and practical implications of the intrinsic subtype classification of breast cancers and the limitations of this approach. It presents the most extensively validated gene expression assays proposed as predictors of clinical outcome and discusses their potential clinical utility and limitations.

Oncology biomarkers: discovery, validation, and clinical use

OBJECTIVES

To discuss the discovery, validation, and clinical use of multiple types of biomarkers.

DATA SOURCES

Medical literature and published guidelines.

CONCLUSION

Formal validation of biomarkers should include both retrospective analyses of well-characterized samples as well as a prospective clinical trial in which the biomarker is tested for its ability to predict the presence of disease or the efficacy of a cancer therapy.

IMPLICATIONS FOR NURSING PRACTICE

Biomarker development is complicated, with very few biomarker discoveries leading to clinically useful tests. Nurses should understand how a biomarker was developed, including the sensitivity and specificity before applying new biomarkers in the clinical setting.

Nomogram to predict the benefit of radiation for older patients with breast cancer treated with conservative surgery

PURPOSE

The role of radiation therapy (RT) after conservative surgery (CS) remains controversial for older patients with breast cancer. Guidelines based on recent clinical trials have suggested that RT may be omitted in selected patients with favorable disease. However, it is not known whether this recommendation should extend to other older women. Accordingly, we developed a nomogram to predict the likelihood of long-term breast preservation with and without RT.

METHODS

We used Surveillance, Epidemiology, and End Results-Medicare data to identify 16,092 women age 66 to 79 years treated with CS between 1992 and 2002, using claims to identify receipt of RT and subsequent mastectomy. Time to mastectomy was estimated using the Kaplan-Meier method. Cox proportional hazards models determined the effect of covariates on mastectomy-free survival (MFS). A nomogram was developed to predict 5- and 10-year MFS, given associated risk factors, and bootstrap validation was performed.

RESULTS

With a median follow-up of 7.2 years, the overall 5- and 10-year MFS rates were 98.1% (95% CI, 97.8% to 98.3%) and 95.4% (95% CI, 94.9% to 95.8%), respectively. In multivariate analysis, age, race, tumor size, estrogen receptor status, and receipt of RT were predictive of time to mastectomy and were incorporated into the nomogram. Nodal status was also included given a significant interaction with RT. The resulting nomogram demonstrated good accuracy in predicting MFS, with a bootstrap-corrected concordance index of 0.66.

CONCLUSION

This clinically useful tool predicts 5- and 10-year MFS among older women with early breast cancer using readily available clinicopathologic factors and can aid individualized clinical decision making by estimating predicted benefit from RT.

Clinical validity/utility, change in practice patterns, and economic implications of risk stratifiers to predict outcomes for early-stage breast cancer: a systematic review

BACKGROUND

At least 14 stratifiers exist to assess recurrence risk, chemotherapy response, and overall survival (OS) in women with early-stage breast cancer (ESBC). These stratifiers have not been compared using a recently developed rigorous framework. We performed a systematic review of the literature on clinical validity/utility, change in clinical practice, and economic implications of ESBC stratifiers.

METHODS

A systematic literature search was performed using PubMed, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and bibliographies of relevant studies. Data were extracted by two investigators and graded using a previously published framework. The Level-of-Evidence determination for each study was summarized, and the studies that provide evidence on change in clinical practice and economic implications are reported.

RESULTS

Fifty-six articles published original evidence addressing the 21-gene recurrence score (n = 31), 70-gene signature (n = 14), Adjuvant! Online (n = 12), 5-antibody immunohistochemistry panel (n = 3), 5-gene expression index (n = 1), and 14-gene signature (n = 1). The 21-gene recurrence score satisfied Level I evidence (the highest level of evidence among five levels) for estimating distant recurrence risk (DRR), OS, and response to adjuvant chemotherapy, and Level II for estimating local recurrence risk. The 5-antibody immunohistochemistry panel and 70-gene signature satisfied Level II evidence for estimating DRR and OS. Adjuvant! Online satisfied Level II evidence for estimating DRR, OS, and chemotherapy response. The 5-gene expression index satisfied Level III evidence for predicting DRR. The 14-gene signature satisfied Level III evidence for predicting DRR and OS. Ten studies reported changes in clinical practice patterns; seven studies reported economic implications.

CONCLUSION

The available evidence on the ability of stratifiers to predict risks of recurrence and response to chemotherapy in ESBC is growing. Level-of-Evidence determinations using the newer framework provide a solid scientific foundation for clinical recommendations.

Why does Oncotype DX recurrence score reduce adjuvant chemotherapy use?

The Oncotype DX recurrence score (RS) reduces breast cancer adjuvant treatment utilization, but the reasons for this effect are not straightforward. We performed a retrospective chart review of 89 consecutive node-negative breast cancer patients for whom RS was ordered to facilitate adjuvant treatment decisions. By subtracting the relapse rate predicted by RS from that calculated using the Adjuvant! Online (AOL) web-based instrument, a "prognostic delta" (P∆) was determined, reflecting the difference between prognoses predicted by these two indices. Clinician interviews were conducted to evaluate the actual effect of RS on treatment decisions and its relation to P∆. Adjuvant chemotherapy use decreased from 61 to 26 % as a consequence of RS results (p < 0.0001). In multivariate analysis, RS was the only factor significantly associated with the final adjuvant treatment choice. Surprisingly, RS caused chemotherapy to be withheld even when P∆ was negative (i.e., cases in which RS predicted a less favorable outcome than AOL). The prognostic and chemotherapy predictive utilities of the RS do not fully account for its effect in reducing adjuvant chemotherapy use. Further studies are required to more fully elucidate other factors that may be responsible for this effect, including the possibility of unintended influence.

Tissue microarray-based study of patients with lymph node-positive breast cancer shows tyrosine phosphorylation of signal transducer and activator of transcription 3 (tyrosine705-STAT3) is a marker of good prognosis

BACKGROUND

Although lymph node-positive breast cancers are associated with poorer prognosis, individual patients may have different clinical outcomes. Signal transducer and activator of transcription 3 (STAT3) is a point of convergence for numerous oncogenic signalling pathways. The goal of this study was to determine the prognostic value of phosphorylated (tyrosine705)-STAT3 in node-positive breast cancer patients.

METHODS

Immunohistochemical analysis of Phospho- STAT3 was performed on a tissue microarray of breast cancer specimens. The expression pattern of Phospho-STAT3 was correlated with survival outcome, and clinical and pathological parameters.

RESULTS

Out of 125 interpretable tumours, positive Phospho- STAT3 nuclear expression was seen in 35 (28%) of tumours. There was no significant relationship between Phospho-STAT3 expression and clinical-pathological parameters including age, hormonal receptor status, grade and tumour size. Interestingly positive tumours had a significantly improved disease-free survival at 5 years (p=0.035). Additionally, positive Phospho-STAT3 nuclear expression was correlated with significantly improved survival at both 5 years (p=0.023) and 10 years (p=0.026). Finally, in multivariate analyses Phospho-STAT3 was found to be an independent prognostic marker of overall survival in node-positive breast cancer patients.

CONCLUSION

These findings support the role of Phospho- STAT3 as an important independent prognostic marker in node-positive breast cancer patients.

Healthcare reform: it is getting personal

Healthcare reform must deal with the challenge of reducing the cost of care while embracing the opportunity to improve care delivery. Personalized medicine will be key to developing new care models. These models will provide coordinated and continuous care delivered by a team, with the individual patient as the central member of the team. Clinical effectiveness research will identify the best care models and reduce variation for populations of patients with a given disease. Personalized medicine will apply 'big science 'omics' with a systems biology approach to define disease networks, allowing us to add back appropriate variation in care for the individual. This effort will be enhanced by the electronic health record, which, combined with deep analytics, will capture detailed phenotypic data matched with the genotype. We are at the beginning of this journey and, despite a variety of technical, economic and societal hurdles, we cannot afford to fail.

Prognostic value of biologic subtype and the 21-gene recurrence score relative to local recurrence after breast conservation treatment with radiation for early stage breast carcinoma: results from the Eastern Cooperative Oncology Group E2197 study

The present study was performed to evaluate the significance of biologic subtype and 21-gene recurrence score relative to local recurrence and local-regional recurrence after breast conservation treatment with radiation. Eastern Cooperative Oncology Group E2197 was a prospective randomized clinical trial that compared two adjuvant systemic chemotherapy regimens for patients with operable breast carcinoma with 1-3 positive lymph nodes or negative lymph nodes with tumor size >1.0 cm. The study population was a subset of 388 patients with known 21-gene recurrence score and treated with breast conservation surgery, systemic chemotherapy, and definitive radiation treatment. Median follow-up was 9.7 years (range = 3.7-11.6 years). The 10-year rates of local recurrence and local-regional recurrence were 5.4 % and 6.6 %, respectively. Neither biologic subtype nor 21-gene Recurrence Score was associated with local recurrence or local-regional recurrence on univariate or multivariate analyses (all P ≥ 0.12). The 10-year rates of local recurrence were 4.9 % for hormone receptor positive, HER2-negative tumors, 6.0 % for triple negative tumors, and 6.4 % for HER2-positive tumors (P = 0.76), and the 10-year rates of local-regional recurrence were 6.3, 6.9, and 7.2 %, respectively (P = 0.79). For hormone receptor-positive tumors, the 10-year rates of local recurrence were 3.2, 2.9, and 10.1 % for low, intermediate, and high 21-gene recurrence score, respectively (P = 0.17), and the 10-year rates of local-regional recurrence were 3.8, 5.1, and 12.0 %, respectively (P = 0.12). For hormone receptor-positive tumors, the 21-gene recurrence score evaluated as a continuous variable was significant for local-regional recurrence (hazard ratio 2.66; P = 0.03). The 10-year rates of local recurrence and local-regional recurrence were reasonably low in all subsets of patients. Neither biologic subtype nor 21-gene recurrence score should preclude breast conservation treatment with radiation.

Assessment of the contribution of the IHC4+C score to decision making in clinical practice in early breast cancer

Background:

The immunohistochemical (IHC) 4+C score is a cost-effective prognostic tool that uses clinicopathologic factors and four standard IHC assays: oestrogen receptor (ER), PR, HER2 and Ki67. We assessed its utility in personalising breast cancer treatment in a clinical practice setting, through comparison with Adjuvant! Online (AoL) and the Nottingham Prognostic Index (NPI).

Methods:

We prospectively gathered clinicopathologic data for postmenopausal patients with hormone receptor-positive, HER2-negative, N0-3 resected early breast cancer treated consecutively at our institution. We retrospectively calculated and compared prognostic scores. The primary endpoint was the proportion of patients reclassified from AoL-defined intermediate-risk by application of the IHC4+C score.

Results:

The median age of the 101 patients included in the analysis was 63. In all, 15 of the 26 patients classified as intermediate-risk by AoL were reallocated to a low-risk group by application of the IHC4+C score and no patient was reclassified as high-risk group. Of the 59 patients classified as intermediate-risk group by the NPI, 24 were reallocated to a low-risk group and 13 to a high-risk group.

Conclusion:

IHC4+C reclassifies more than half of the patients stratified as being in intermediate-risk group by the AoL and NPI. The use of IHC4+C may substantially improve decision-making on adjuvant chemotherapy.

Prospective transGEICAM study of the impact of the 21-gene Recurrence Score assay and traditional clinicopathological factors on adjuvant clinical decision making in women with estrogen receptor-positive (ER+) node-negative breast cancer

BACKGROUND

This study examined the impact of the Recurrence Score (RS) in Spanish breast cancer patients and explored the associations between clinicopathological markers and likelihood of change in treatment recommendations.

PATIENTS AND METHODS

Enrollment was offered consecutively to eligible women with estrogen receptor-positive; human epidermal growth factor receptor 2-negative, node-negative breast cancer. Oncologists recorded treatment recommendation and confidence in it before and after knowing the patient's RS.

RESULTS

Treatment recommendation changed in 32% of 107 patients enrolled: in 21% from chemohormonal (CHT) to hormonal therapy (HT) and in 11% from HT to CHT. RS was associated with the likelihood of change from HT to CHT (P < 0.001) and from CHT to HT (P < 0.001). Confidence of oncologists in treatment recommendations increased for 60% of cases. Higher tumor grade (P = 0.007) and a high proliferative index (Ki-67) (P = 0.023) were significantly associated with a greater chance of changing from HT to CHT, while positive progesterone receptor status (P = 0.002) with a greater probability of changing from CHT to HT.

CONCLUSIONS

Results from the first prospective European study are consistent with published experience and use of the RS as proposed in European clinical practice guidelines and provide evidence on how Oncotype DX and clinicopathological factors are complementary and patient selection may be improved.

Molecular classification of estrogen receptor-positive/luminal breast cancers

Estrogen receptor (ER)-positive breast cancer is the most prevalent subtype of invasive breast cancers. Patients with ER-positive breast cancers have variable clinical outcomes and responses to endocrine therapy and chemotherapy. With the advent of microarray-based gene expression profiling, unsupervised analysis methods have resulted in a classification of ER-positive disease into subtypes with different outcomes (ie, luminal A and luminal B); subsequent studies have demonstrated that these subtypes have different patterns of genetic aberrations and outcome. Studies based on supervised methods of microarray analysis have led to the development of prognostic gene signatures that identify a subgroup of ER-positive breast cancer patients with excellent outcome, who could forego chemotherapy. Despite the excitement with these approaches, several lines of evidence have demonstrated that the subclassification of ER-positive cancers and the prognostic value of gene signatures is largely driven by the expression levels of proliferation-related genes and that proliferation markers, such as Ki67, may provide equivalent prognostic information to that provided by gene signatures. In this review, we discuss the contribution of gene expression profiling to the classification of ER-positive breast cancer, the role of prognostic and predictive signatures, and the potential stratification of ER-positive disease according to their dependency on the phosphatidylinositol 3-kinase pathway.

Knowledge about genomic recurrence risk testing among breast cancer survivors

Genomic expression profiling of tumors is used to individualize early-stage breast cancer treatment. However, very little is known about patients' understanding of and desired information about these tests, such as Oncotype DX. We addressed these issues via a survey mailed to 130 early-stage breast cancer patients who received an Oncotype DX test result. The survey assessed understanding (14 items), information desired about genomic expression profiling tests, and if and where they sought information about Oncotype DX. Sixty-four surveys were returned. Overall, 54% of the knowledge items were answered correctly. Patients wanted education about genomic tests in many areas. Overall, 62% sought information about the test, primarily from the Internet (48%) and doctor or health care provider (31%). In sum, patients' misunderstanding of genomic tests abound, necessitating better educational efforts on behalf of health care systems to meet their needs for varied information through different communication channels.

Risk of recurrence and chemotherapy benefit for patients with node-negative, estrogen receptor-positive breast cancer: recurrence score alone and integrated with pathologic and clinical factors

PURPOSE

The 21-gene breast cancer assay recurrence score (RS) is widely used for assessing recurrence risk and predicting chemotherapy benefit in patients with estrogen receptor (ER) -positive breast cancer. Pathologic and clinical factors such as tumor size, grade, and patient age also provide independent prognostic utility. We developed a formal integration of these measures and evaluated its prognostic and predictive value.

PATIENTS AND METHODS

From the National Surgical Adjuvant Breast and Bowel (NSABP) B-14 and translational research cohort of the Arimidex, Tamoxifen Alone or in Combination (TransATAC) studies, we included patients who received hormonal monotherapy, had ER-positive tumors, and RS and traditional clinicopathologic factors assessed (647 and 1,088, respectively). Individual patient risk assessments from separate Cox models were combined using meta-analysis to form an RS-pathology-clinical (RSPC) assessment of distant recurrence risk. Risk assessments by RS and RSPC were compared in node-negative (N0) patients. RSPC was compared with RS for predicting chemotherapy benefit in NSABP B-20.

RESULTS

RSPC had significantly more prognostic value for distant recurrence than did RS (P < .001) and showed better separation of risk in the study population. RSPC classified fewer patients as intermediate risk (17.8% v 26.7%, P < .001) and more patients as lower risk (63.8% v 54.2%, P < .001) than did RS among 1,444 N0 ER-positive patients. In B-20, the interaction of RSPC with chemotherapy was not statistically significant (P = .10), in contrast to the previously reported significant interaction of RS with chemotherapy (P = .037).

CONCLUSION

RSPC refines the assessment of distant recurrence risk and reduces the number of patients classified as intermediate risk. Adding clinicopathologic measures did not seem to enhance the value of RS alone nor the individual biology RS identifies in predicting chemotherapy benefit.

Relationship between quantitative GRB7 RNA expression and recurrence after adjuvant anthracycline chemotherapy in triple-negative breast cancer

PURPOSE

To conduct an exploratory analysis of the relationship between gene expression and recurrence in patients with operable triple-negative breast cancer (TNBC) treated with adjuvant doxorubicin-containing chemotherapy.

EXPERIMENTAL DESIGN

RNA was extracted from archived tumor samples derived from 246 patients with stage I-III TNBC treated with adjuvant doxorubicin-containing chemotherapy, and was analyzed by quantitative reverse transcriptase PCR for a panel of 374 genes. The relationship between gene expression and recurrence was evaluated using weighted Cox proportional hazards model score tests.

RESULTS

Growth factor receptor bound protein 7 (GRB7) was the only gene for which higher expression was significantly associated with increased recurrence in TNBC (Korn's adjusted P value = 0.04). In a Cox proportional hazards model adjusted for clinicopathologic features, higher GRB7 expression was associated with an increased recurrence risk (HR = 2.31; P = 0.04 using the median as the split). The 5-year recurrence rates were 10.5% [95% confidence intervals (CI), 7.8-14.1] in the low and 20.4% (95% CI, 16.5-25.0) in the high GRB7 groups. External validation in other datasets indicated that GRB7 expression was not prognostic in two adjuvant trials including variable systemic therapy, but in two other trials showed that high GBR7 expression was associated with resistance to neoadjuvant doxorubicin and taxane therapy.

CONCLUSIONS

GRB7 was associated with an increased risk of recurrence in TNBC, suggesting that GRB7 or GRB7-dependent pathways may serve as potential biomarkers for therapeutic targets. Therapeutic targeting of one or more factors identified which function as interaction nodes or effectors should also be considered.

Predictive and prognostic molecular markers for cancer medicine

Over the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive tests are still being developed. Similarly, the science of using tumor molecular profiles to select clinical trial participants or to optimize therapy for individual patients is still in its infancy. This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold. It will also highlight the potential importance of methods that can integrate molecular, histopathological and clinical information into a synergistic understanding of tumor progression. While these possibilities are without doubt exciting, significant challenges remain if we are to implement them with a strong evidence base in a widely available and cost-effective manner.

Prognostic utility of the breast cancer index and comparison to Adjuvant! Online in a clinical case series of early breast cancer

INTRODUCTION

Breast Cancer Index (BCI) combines two independent biomarkers, HOXB13:IL17BR (H:I) and the 5-gene molecular grade index (MGI), that assess estrogen-mediated signalling and tumor grade, respectively. BCI stratifies early-stage estrogen-receptor positive (ER+), lymph-node negative (LN-) breast cancer patients into three risk groups and provides a continuous assessment of individual risk of distant recurrence. Objectives of the current study were to validate BCI in a clinical case series and to compare the prognostic utility of BCI and Adjuvant!Online (AO).

METHODS

Tumor samples from 265 ER+LN- tamoxifen-treated patients were identified from a single academic institution's cancer research registry. The BCI assay was performed and scores were assigned based on a pre-determined risk model. Risk was assessed by BCI and AO and correlated to clinical outcomes in the patient cohort.

RESULTS

BCI was a significant predictor of outcome in a cohort of 265 ER+LN- patients (median age: 56-y; median follow-up: 10.3-y), treated with adjuvant tamoxifen alone or tamoxifen with chemotherapy (32%). BCI categorized 55%, 21%, and 24% of patients as low, intermediate and high-risk, respectively. The 10-year rates of distant recurrence were 6.6%, 12.1% and 31.9% and of breast cancer-specific mortality were 3.8%, 3.6% and 22.1% in low, intermediate, and high-risk groups, respectively. In a multivariate analysis including clinicopathological factors, BCI was a significant predictor of distant recurrence (HR for 5-unit increase = 5.32 [CI 2.18-13.01; P = 0.0002]) and breast cancer-specific mortality (HR for a 5-unit increase = 9.60 [CI 3.20-28.80; P < 0.0001]). AO was significantly associated with risk of recurrence. In a separate multivariate analysis, both BCI and AO were significantly predictive of outcome. In a time-dependent (10-y) ROC curve accuracy analysis of recurrence risk, the addition of BCI+AO increased predictive accuracy in all patients from 66% (AO only) to 76% (AO+BCI) and in tamoxifen-only treated patients from 65% to 81%.

CONCLUSIONS

This study validates the prognostic performance of BCI in ER+LN- patients. In this characteristically low-risk cohort, BCI classified high versus low-risk groups with ~5-fold difference in 10-year risk of distant recurrence and breast cancer-specific death. BCI and AO are independent predictors with BCI having additive utility beyond standard of care parameters that are encompassed in AO.

Comparison between Oncotype DX test and standard prognostic criteria in estrogen receptor positive early-stage breast cancer

ABSTRACT Objective: To compare the prognosis estimated by standard prognostic criteria versus the prognosis estimated by the Oncotype DX. Methods: A retrospective study was performed on 22 patients with positive estrogen receptor, early-stage breast cancer who had an Oncotype DX recurrence score available. Results: Kappa value between Oncotype DX and standard prognostic criteria was: Adjuvant! (K = 0.091), Adjuvant! (Transbig) (K = 0.182) and National Comprehensive Cancer Network (K = 0.091). The Fisher's exact test did not show correlation between Oncotype and standard prognostic criteria. Conclusion: Standard prognostic criteria showed no correlation with Oncotype DX.

Cancer clinical trials in the era of genomic signatures: biomedical innovation, clinical utility, and regulatory-scientific hybrids

The paper examines two large-scale, North American and European clinical trials designed to validate two commercially available genomic tumor signatures that predict a patient's risk of breast cancer recurrence and response to chemotherapy. The paper builds on empirical evidence from the two trials to explore the emergence of diverse regulatory-scientific hybrids; that is, the paper discusses configurations of genomic practice and bioclinical work that depend on linkages between technical, commercial, patient, clinical, and legal interests and institutions. The development of the genomic signatures for each trial--Oncotype DX and MammaPrint--has followed quite different routes. Oncotype began as a commercial platform: the company that produced it did not discover a signature but rather constructed it by asking users at every step what clinical question they wanted the signature to answer and what data would be credible in that regard. The test has been designed to minimally disrupt existing clinical workflows. MammaPrint, on the other hand, began as a breast cancer signature: the researchers who discovered it, at the Netherlands Cancer Institute (NKI), established a company to commercialize it as a test after the fact. MammaPrint requires a change in pathologists' routines. Thus, while these two trials signify a new departure for clinical cancer trials on a number of levels--they both incorporate new models of interaction between biotech companies and public research, and they both aim to establish the clinical relevance of genomic markers--they also embody different socio-technical scripts: one attempts to accommodate established routines, while the other openly challenges prevailing evidential hierarchies and existing biomedical configurations.

Personalized medicine: the road ahead

With breast cancer now being recognized as a heterogeneous disease, the concept of personalized medicine demands that the tumor of every individual be treated uniquely. This has lead to ever-expanding use of existing prognostic and predictive markers, and the search for better ones is ongoing. The classic prognostic tools such as tumor size, lymph node status, grade, hormone receptors, and HER2 status are now supplemented by gene expression-based tools such as PAM50 and MammaPrint. However, the overdependence of these tools on proliferation-related genes is a significant handicap. Although pathway-based signatures hold great promise in future breast cancer prognostication, the fact that every tumor has multiple functional pathways significantly limits the utility of this approach. Developed by the integration of estrogen receptor (ER), HER2, proliferation-related, and other genes, the Oncotype DX assay has been able to provide valuable prognostic information for ER-positive tumors. Newer molecular markers based on cancer stem cells, single-nucleotide polymorphisms (SNPs), and miRNAs are becoming available, but their importance needs to be validated. It is clear that breast cancer is a multifaceted process and that none of the tools can reliably predict a binary outcome (recurrence or no recurrence). The breast cancer community is still awaiting an ideal prognostic tool that can integrate knowledge from classic variables such as tumor size and grade with new throughput technology and principles of pharmacogenomics. Such a tool will not only define prognostic subgroups but also be able to predict therapeutic efficacy and/or resistance based on molecular profiling.

Gene expression profiling for breast cancer prognosis in Chinese populations

To investigate a quantitative reverse transcription polymerase chain reaction (QRT-PCR) assay different from 21-gene assay which can be used to prognosticate the risk of recurrence in patients with estrogen receptor (ER) positive, lymph node (LN) negative breast cancer. To accurately determine the relationship between the Recurrence Score (RS) derived from our assay and the risk of distant recurrence in Chinese patients with LN negative and positive breast cancer through the analysis of paraffin tissues. We obtained archival paraffin-embedded tissues from patients with invasive breast cancer and varying axillary lymph node involvement. QRT-PCR reaction was performed by using the method of SYBR Green I dye with primers. Expression of the 21-genes was converted to RS by a prespecified algorithm. We then assessed the probability of the test to accurately predict distant recurrence-free survival in this retrospective cohort. Ninety-three patients were eligible based on gene expression profiles. In our population, most breast cancer patients were premenopausal (82.6%), at early stage (93.6%) and ER positive (91.4%). Median follow-up was 65.9 months. The 5-year recurrence-free survival rate for the group was 58.8%. The concordance between the reverse transcription-PCR and immunohistochemical (IHC) measurement for ER, progesterone receptor (PgR), and HER-2 determinations was high and comparable. High RS was predictive of an elevated risk of relapse (p < 0.001). In subgroups of patients, RS had significantly predictive performance both in node-negative (p = 0.009) and node-positive patients (p = 0.038). Multivariable analysis showed that nodal status, adjuvant hormonal therapy and RS were significantly related to prognosis. RS category is a better predictor than the other risk assessment criteria or clinicopatholic features, with which we can determine more accurately the risks for recurrence of various patients. We have established an easy and economical QRT-PCR assay and validated in concordance with IHC measurements for ER, PgR, and HER-2. RS was associated with distant recurrence among Chinese patients with hormone receptor (HR) positive breast cancer. This study may promote the use of RS estimated from the expression of the 21-gene set for prognostication and routine clinical diagnostic application in Chinese populations.

Physician survey of the effect of the 21-gene recurrence score assay results on treatment recommendations for patients with lymph node-positive, estrogen receptor-positive breast cancer

PURPOSE

To survey the effect of the 21-gene recurrence score (RS) assay results on adjuvant treatment recommendations for patients with lymph node-positive (N+), estrogen receptor-positive (ER+) breast cancer.

METHODS

Medical oncologists who ordered the 21-gene RS assay were invited to complete a survey regarding their most recent patient with N+/ER+ breast cancer. We obtained responses from 160 (16%) of the 1,017 medical oncologists.

RESULTS

Most of the respondents were in community (71%) versus academic (25%) settings and had practiced for a median of 11 years. T1, T2, or T3 disease was reported in 62%, 35%, and 3% of patients, respectively. One, two, three, or ≥ 4 nodes were reported in 69%, 18%, 6%, and 3% of patients, respectively. Eighty-six percent of the oncologists made treatment recommendations before obtaining the RS; 51% changed their recommendations after receiving the RS. In 33%, treatment intensity decreased from chemotherapy plus hormonal therapy to hormonal therapy alone. In 9%, treatment intensity increased from hormonal therapy alone to chemotherapy plus hormonal therapy. In 8%, treatment recommendations changed in a way that did not fit the definition of either increased or decreased intensity.

CONCLUSION

In this survey of physician practice, the RS result was used to guide adjuvant treatment decision making in N+/ER+ breast cancer more often in patients with tumors less than 5 cm in size and one to three positive lymph nodes than in patients with larger tumors and four or more positive nodes and yielded an overall reduction in recommendations for chemotherapy.

Quantum dots-based molecular classification of breast cancer by quantitative spectroanalysis of hormone receptors and HER2

The emerging molecular breast cancer (BC) classification based on key molecules, including hormone receptors (HRs), and human epidermal growth factor receptor 2 (HER2) has been playing an important part of clinical practice guideline. The current molecular classification mainly based on their fingerprints, however, could not provide enough essential information for treatment decision making. The molecular information on both patterns and quantities could be more helpful to heterogeneities understanding for BC personalized medicine. Here we conduct quantitative determination of HRs and HER2 by quantum dots (QDs)-based quantitative spectral analysis, which had excellent consistence with traditional method. Moreover, we establish a new molecular classification system of BC by integrating the quantitative information of HER2 and HRs, which could better reveal BC heterogeneity and identify 5 molecular subtypes with different 5-year prognosis. Furthermore, the emerging 5 molecular subtypes based on simple quantitative molecules information could be as informative as multi-genes analysis in routine practice, and might help formulate a more personalized comprehensive therapy strategy and prognosis prediction.

Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management.

Gene expression profile testing for breast cancer and the use of chemotherapy, serious adverse effects, and costs of care

As gene expression profile (GEP) testing for breast cancer may provide additional prognostic information to guide the use of adjuvant chemotherapy, we examined the association between GEP testing and use of chemotherapy, serious chemotherapy-related adverse effects, and total charges during the 12 months following diagnosis. Medical record review was conducted for women age 30-64 years, with incident, non-metastatic, invasive breast cancer diagnosed 2006-2008 in a large, national health plan. Of 534 patients, 25.8% received GEP testing, 68.2% received chemotherapy, and 10.5% experienced a serious chemotherapy-related adverse effect. GEP testing was most commonly used in women at moderate clinical risk of recurrence (52.0 vs. 25.0% of low-risk women and 5.5% of high-risk). Controlling for the propensity to receive GEP testing, women who had GEP were less likely to receive chemotherapy (propensity adjusted odds ratio, 95% confidence interval 0.62, 0.39-0.99). Use of GEP was associated with more chemotherapy use among women at low risk based on clinical characteristics (OR = 42.19; CI 2.50-711.82), but less use among women with a high risk based on clinical characteristics (OR = 0.12; CI 0.03-0.47). Use of GEP was not associated with chemotherapy for the moderate risk group. There was no significant relationship between GEP use and either serious chemotherapy-associated adverse effects or total charges. While GEP testing was associated with an overall decrease in adjuvant chemotherapy, we did not find differences in serious chemotherapy-associated adverse events or charges during the 12 months following diagnosis.

A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer

CONTEXT

Prediction of high probability of survival from standard cancer treatments is fundamental for individualized cancer treatment strategies.

OBJECTIVE

To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer.

DESIGN, SETTING, AND PATIENTS

Prospective multicenter study conducted from June 2000 to March 2010 at the M. D. Anderson Cancer Center to develop and test genomic predictors for neoadjuvant chemotherapy. Patients were those with newly diagnosed ERBB2 (HER2 or HER2/neu)-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens (then endocrine therapy if estrogen receptor [ER]-positive). Different predictive signatures for resistance and response to preoperative (neoadjuvant) chemotherapy (stratified according to ER status) were developed from gene expression microarrays of newly diagnosed breast cancer (310 patients). Breast cancer treatment sensitivity was then predicted using the combination of signatures for (1) sensitivity to endocrine therapy, (2) chemoresistance, and (3) chemosensitivity, with independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response.

MAIN OUTCOME MEASURES

Distant relapse-free survival (DRFS) if predicted treatment sensitive and absolute risk reduction ([ARR], difference in DRFS between 2 predicted groups) at median follow-up (3 years).

RESULTS

Patients in the independent validation cohort (99% clinical stage II-III) who were predicted to be treatment sensitive (28%) had 56% (95% CI, 31%-78%) probability of excellent pathologic response and DRFS of 92% (95% CI, 85%-100%), with an ARR of 18% (95% CI, 6%-28%). Survival was predicted in ER-positive (30% predicted sensitive; DRFS, 97% [95% CI, 91%-100%]; ARR, 11% [95% CI, 0.1%-21%]) and ER-negative (26% predicted sensitive; DRFS, 83% [95% CI, 68%-100%]; ARR, 26% [95% CI, 4%-48%]) subsets and was significant in multivariate analysis. Other genomic predictors showed paradoxically worse survival for patients predicted to be responsive to chemotherapy.

CONCLUSION

A genomic predictor combining ER status, predicted chemoresistance, predicted chemosensitivity, and predicted endocrine sensitivity identified patients with high probability of survival following taxane and anthracycline chemotherapy.

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.

Genomic testing and therapies for breast cancer in clinical practice

PURPOSE

Given the likely proliferation of targeted testing and treatment strategies for cancer, a better understanding of the utilization patterns of human epidermal growth factor receptor 2 (HER2) testing and trastuzumab and newer gene expression profiling (GEP) for risk stratification and chemotherapy decision making are important.

STUDY DESIGN

Cross-sectional.

METHODS

We performed a medical record review of women age 35 to 65 years diagnosed between 2006 and 2007 with invasive localized breast cancer, identified using claims from a large national health plan (N = 775).

RESULTS

Almost all women received HER2 testing (96.9%), and 24.9% of women with an accepted indication received GEP. Unexplained socioeconomic differences in GEP use were apparent after adjusting for age and clinical characteristics; specifically, GEP use increased with income. For example, those in the lowest income category (< $40,000) were less likely than those with an income of $125,000 or more to receive GEP (odds ratio, 0.34; 95% CI, 0.16 to 0.73). A majority of women (57.7%) with HER2-positive disease received trastuzumab; among these women, differences in age and clinical characteristics were not apparent, although surprisingly, those in the lowest income category were more likely than those in the high-income category to receive trastuzumab (P = .02). Among women who did not have a positive HER2 test, 3.9% still received trastuzumab. Receipt of adjuvant chemotherapy increased as GEP score indicated greater risk of recurrence.

CONCLUSION

Identifying and eliminating unnecessary variation in the use of these expensive tests and treatments should be part of quality improvement and efficiency programs.

Metastasis-suppressor genes in clinical practice: lost in translation?

Over the past 25 years, an expanding set of metastasis-suppressor genes (MSGs) has been identified that specifically regulate metastasis formation without affecting primary growth. MSGs are involved in diverse molecular processes in multiple tumor types. Given the wealth of metastasis biology that underlies their functions, treatment strategies based on MSGs have an unparalleled potential to improve patient care. Using NM23 as a prime example, we discuss how specific MSGs have been used as prognostic markers, tools for predicting response to treatment, and targets for the development of novel therapies. Barriers specific to the translation of MSG biology into clinical practice are reviewed and future research directions necessary for clinical advances are delineated. Although to date the impact of MSGs on patient care is limited, it is an expanding field with vast potential to help develop new treatments and identify patients who will most benefit from them.

Plasma markers for identifying patients with metastatic melanoma

PURPOSE

With the rising incidence of melanoma, more patients are undergoing surveillance for disease recurrence. Our purpose was to study levels of proteins that might be secreted in the blood of patients with metastatic melanoma that can be used for monitoring these individuals.

METHODS

Genome-wide gene expression data were used to identify abundantly expressed genes in melanoma cells that encode for proteins likely to be present in the blood of cancer patients, based on high expression levels in tumors. ELISA assays were employed to measure proteins in plasma of 216 individuals; 108 metastatic melanoma patients and 108 age- and gender-matched patients with resected stage I/II disease split into equal-sized training and test cohorts.

RESULTS

Levels of seven markers, CEACAM (carcinoembryonic antigen-related cell adhesion molecule), ICAM-1 (intercellular adhesion molecule 1), osteopontin, MIA (melanoma inhibitory activity), GDF-15 (growth differentiation factor 15), TIMP-1 (tissue inhibitor of metalloproteinase 1), and S100B, were higher in patients with unresected stage IV disease than in patients with resected stage I/II disease. About 81% of the stage I/II patients in the training set had no marker elevation, whereas 69% of the stage IV patients had elevation of at least one marker (P < 0.0001). Receiver operating characteristic curves for the markers in combination in these two patient populations had an area under curve (AUC) of 0.79 in the training set and 0.8 in the test set. A CART (Classification and Regression Trees) model developed in the training set further improved the AUC in the test set to 0.898.

CONCLUSIONS

Plasma markers, particularly when assessed in combination, can be used to monitor patients for disease recurrence and can compliment currently used lactate dehydrogenase and imaging studies; prospective validation is warranted.

Knowledge of genomic testing among early-stage breast cancer patients

BACKGROUND

Genomic recurrence risk test results now inform clinical decisions about adjuvant treatment for women with early-stage breast cancer. We sought to understand patients' knowledge of these tests and correlates of their knowledge.

METHODS

Participants in this cross-sectional study were 78 women, treated for early-stage, estrogen receptor-positive breast cancer with 0-3 positive lymph nodes, whose medical records indicated they received Oncotype DX testing earlier. We mailed a questionnaire that assessed knowledge of genomic recurrence risk testing (13 item scale, alpha=0.83) and reviewed medical charts of consenting patients.

RESULTS

Knowledge about genomic recurrence risk testing was low (mean knowledge score=67%, SD=0.23). Low knowledge scores were more commonly due to responses of 'don't know' than incorrect answers. Most women (91%) clearly understood that test results can aid decisions about chemotherapy, and few (22%) understood that the test's estimate of the chance of metastasis assumes the patient is receiving hormone therapy. Higher knowledge about genomic recurrence risk testing was associated with higher education, reading ability, and numeracy. Knowledge was higher among women who recalled receiving both verbal and printed information about the test and among women who had active roles in deciding about their treatments. Higher knowledge was also associated with having fewer concerns about genomic testing.

DISCUSSION

Among early-stage breast cancer patients who received Oncotype DX, we found low knowledge about many aspects of genomic recurrence risk testing. Research is needed to understand testing information provided to patients and best practices for patient education.

The impact of the 21-gene recurrence score assay on decision making about adjuvant chemotherapy in early-stage estrogen-receptor-positive breast cancer in an oncology practice with a unified treatment policy

BACKGROUND

The 21-gene recurrence score (RS) assay has been validated in retrospective studies as prognostic of distant disease recurrence and predictive of the benefit of adjuvant chemotherapy in estrogen-receptor-positive breast cancer (BC). There is limited published data on the impact of the assay on clinical practice, particularly in the context of a single practice with a unified treatment policy.

PATIENTS AND METHODS

Between 2006 and 2009, RS was obtained on 135 patients in a single practice with a uniform treatment policy. Treatment recommendations before and after RS result were analyzed retrospectively. Pre-RS treatment recommendations were based on clinicopathological features and Adjuvant! Online (AO) calculated survival advantage. RS and AO survival advantage for adding chemotherapy were compared for each patient.

RESULTS

The distribution by risk group of RS was low- 49.6%, intermediate-37.8%, and high-12.6%. In 34 patients (25.2%, 95% confidence interval 17.9% to 32.5%), recommendation for chemotherapy was changed after obtaining assay result. Most changes (70.6%) were from chemotherapy to no chemotherapy. The RS correlated poorly with AO predictions.

CONCLUSION

The 21-gene assay, when applied in a consistent manner in early-stage BC, changes treatment recommendations in one-quarter of patients tested.

Comparison of the prognostic and predictive utilities of the 21-gene Recurrence Score assay and Adjuvant! for women with node-negative, ER-positive breast cancer: results from NSABP B-14 and NSABP B-20

The Oncotype DX Recurrence Score (RS) is a validated genomic predictor of outcome and response to adjuvant chemotherapy in ER-positive breast cancer. Adjuvant! was developed using SEER registry data and results from the Early Breast Cancer Clinical Trialists' overview analyses to estimate outcome and benefit from adjuvant hormonal therapy and chemotherapy. In this report we compare the prognostic and predictive utility of these two tools in node-negative, ER-positive breast cancer. RS and Adjuvant! results were available from 668 tamoxifen-treated NSABP B-14 patients, 227 tamoxifen-treated NSABP B-20 patients, and 424 chemotherapy plus tamoxifen-treated B-20 patients. Adjuvant! results were also available from 1952 B-20 patients. The primary endpoint was distant recurrence-free interval (DRFI). Cox proportional hazards models were used to compare the prognostic and predictive utility of RS and Adjuvant!. Both RS (P < 0.001) and Adjuvant! (P = 0.002) provided strong independent prognostic information in tamoxifen-treated patients. Combining RS and individual clinicopathologic characteristics provided greater prognostic discrimination than combining RS and the composite Adjuvant!. In the B-20 cohort with RS results (n = 651), RS was significantly predictive of chemotherapy benefit (interaction P = 0.031 for DRFI, P = 0.011 for overall survival [OS], P = 0.082 for disease-free survival [DFS]), but Adjuvant! was not (interaction P = 0.99, P = 0.311, and P = 0.357, respectively). However, in the larger B-20 sub-cohort (n = 1952), Adjuvant! was significantly predictive of chemotherapy benefit for OS (interaction P = 0.009) but not for DRFI (P = 0.219) or DFS (P = 0.099). Prognostic estimates can be optimized by combining RS and clinicopathologic information instead of simply combining RS and Adjuvant!. RS should be used for estimating relative chemotherapy benefit.

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

BACKGROUND

Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.

METHODS

Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.

RESULTS

We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.

CONCLUSIONS

Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.