Comparison of efficacy of 95-gene and 21-gene classifier (Oncotype DX) for prediction of recurrence in ER-positive and node-negative breast cancer patients

Investigation of recurrence prediction ability of EndoPredict® using microarray data from fresh frozen tissues in ER-positive, HER2-negative breast cancer and indication expansion of EndoPredict® from microarray data from fresh-frozen to FFPE tissues

BACKGROUND

EndoPredict® (EP) is a multigene assay to predict distant recurrence risk in luminal breast cancer. EP measures the expression of 12 genes in primary tumor by qRT-PCR from formalin-fixed paraffin-embedded (FFPE) tissues and calculates EP risk score that indicates the risk of distant recurrence. We evaluated the performance of EP in predicting distant recurrence risk using microarray data from fresh frozen (FF) tissues. We also examined the applicability of EP to microarray data from FFPE tissues.

METHODS

We analyzed the publicly available data of 431 node-negative and 270 node-positive patients with luminal breast cancer who received endocrine therapy alone. We evaluated the prognostic value of EP using microarray data from FF tissues. Next, we created an algorithm to calculate EP risk score using microarray data from FFPE tissues. We examined the correlation coefficient of EP risk score and concordance rate of EP risk high/low using microarray data from FFPE/FF tissue pairs in a validation set of 39 patients.

RESULTS

In 431 node-negative patients, the distant recurrence-free survival (DRFS) rate was significantly worse in those with high EP risk scores (P = 3.68 × 10-6, log-rank). The 5-year DRFS was 95.2% in those with low EP risk score. In the validation set, the correlation coefficient of EP risk score was 0.93 and the concordance rate of EP risk high/low was 91.7%.

CONCLUSIONS

EP using microarray data from FF tissues was useful in predicting distant recurrence risk in luminal breast cancer, and EP might be utilized in microarray data from FFPE tissues.

Multi-gene assay 95- and 155-gene classifiers for prognosis prediction and chemotherapy omission in lymphnode positive luminal-type breast cancer

BACKGROUND

The prognosis of lymphnode positive breast cancer is worse than that of lymph node negative breast cancer but some cases may not require chemotherapy. We investigated the ability of the new multi-gene assays, 95GC and 155GC, to identify patients with lymphnode positive Luminal-type breast cancer whose chemotherapy can be omitted relatively safely.

PATIENTS AND METHODS

We extracted 1721 cases of lymphnode positive Luminal-type breast cancer from 22 public database Caucasoid cohorts and 3 Asian cohorts, and performed recurrence prognosis analysis with 95GC and 155GC.

RESULTS

Using 95GC, the cases were stratified as the high (n = 917) and low (n = 202) groups according to the prognosis of lymphnode positive Luminal-type endocrine only breast cancer. The 5 years DRFS in the low risk group was relatively good at 90%, and no additional effect of chemotherapy was observed, suggesting omission of chemotherapy. The recurrence prognosis was also significantly dichotomized into the high and low risks by 95GC in 21GC RS 0-25 cases. Here, we found a group with poor prognosis even in post-menopause RS 0-25 and requiring chemotherapy. Additionally, a group in which the prognosis was good in pre-menopause RS 0-25, and the omission of chemotherapy could be considered. Patients in the high-risk group at 155GC had poor prognosis after chemotherapy. 155GC also showed a group that chemotherapy alone was not sufficient.

CONCLUSION

In this study, we demonstrated the possibility of accurately selecting patient groups for which chemotherapy can be omitted from lymphnode positive Luminal-type breast cancer.

The Rochester Modified Magee Algorithm (RoMMa): An Outcomes Based Strategy for Clinical Risk-Assessment and Risk-Stratification in ER Positive, HER2 Negative Breast Cancer Patients Being Considered for Oncotype DX® Testing

INTRODUCTION

Multigene genomic profiling has become the standard of care in the clinical risk-assessment and risk-stratification of ER⁺, HER2^- breast cancer (BC) patients, with Oncotype DX^® (ODX) emerging as the genomic profile test with the most support from the international community. The current state of the health care economy demands that cost-efficiency and access to testing must be considered when evaluating the clinical utility of multigene profile tests such as ODX. Several studies have suggested that certain lower risk patients can be identified more cost-efficiently than simply reflexing all ER⁺, HER2^- BC patients to ODX testing. The Magee equations^TM use standard histopathologic data in a set of multivariable models to estimate the ODX recurrence score. Our group published the first outcome data in 2019 on the Magee equations^TM, using a modification of the Magee equations^TM combined with an algorithmic approach-the Rochester Modified Magee algorithm (RoMMa). There has since been limited published outcome data on the Magee equations^TM. We present additional outcome data, with considerations of the TAILORx risk-stratification recommendations.

METHODS

355 patients with an ODX recurrence score, and at least five years of follow-up or a BC recurrence were included in the study. All patients received either Tamoxifen or an aromatase inhibitor. None of the patients received adjuvant systemic chemotherapy.

RESULTS

There was no significant difference in the risk of recurrence in similar risk categories (very low risk, low risk, and high risk) between the average Modified Magee score and ODX recurrence score with the chi-square test of independence (p > 0.05) or log-rank test (p > 0.05). Using the RoMMa, we estimate that at least 17% of individuals can safely avoid ODX testing.

CONCLUSION

Our study further reinforces that BC patients can be confidently stratified into lower and higher-risk recurrence groups using the Magee equations^TM. The RoMMa can be helpful in the initial clinical risk-assessment and risk-stratification of BC patients, providing increased opportunities for cost savings in the health care system, and for clinical risk-assessment and risk-stratification in less-developed geographies where multigene testing might not be available.

Racial differences in predictive value of the 21-gene recurrence score assay: a population-based study using the SEER database

Purpose

The 21-gene recurrence score (RS) assay is currently used for predicting chemotherapeutic benefits for hormone receptor-positive (HR +) early-stage breast cancer patients without consideration regarding racial differences in that predictive value. This study aimed at demonstrating racial differences in the predictive values of the 21-gene RS assay.

Methods

The study cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) database. Breast cancer-specific mortality (BCSM) was compared between patients who received chemotherapy (the “CTx group”) and those who did not (the “no CTx group”) to estimate the predictive value of the assay. This comparison was repeated for each racial group.

Results

Among 88,498 T1 − 2N0 HR + breast cancer patients who had results of 21-gene RS, 13,123 patients had RS > 25, which included 10,697 Whites, 1282 Blacks, and 1,144 Asian Americans/Pacific Islanders (AAPIs). Chemotherapy was administered to 8364 patients (63.4%). The adjusted hazard ratio for BCSM in the CTx group (vs. no CTx group) was 0.734 (95% confidence interval [CI] 0.588–0.917) in Whites, 0.748 (95% CI 0.428–1.307) in Blacks, and 1.343 (95% CI 0.558–3.233) in AAPIs. No subgroup within patients with RS > 25 among non-White women showed a significant predictive value of the 21-gene RS assay, except for Black women with grade 3 tumors.

Conclusion

The predictive value of the 21-gene RS assay for assessing chemotherapy benefit was validated in White women based on the SEER database, although the predictive value was not warranted in non-White women.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12282-022-01371-z.

Multicenter retrospective study on the use of Curebest™ 95GC Breast for estrogen receptor-positive and node-negative early breast cancer

Background

The benefits of postoperative chemotherapy in patients with estrogen receptor (ER)-positive breast cancer remain unclear. The use of tumor grade, Ki-67, or ER expression failed to provide an accurate prognosis of the risk of relapse after surgery in patients. This study aimed to evaluate whether a multigene assay Curebest™ 95GC Breast (95GC) can identify the risk of recurrence and provide more insights into the requirements for chemotherapy in patients.

Methods

This single-arm retrospective multicenter joint study included patients with ER-positive, node-negative breast cancer who were treated at five facilities in Japan and had received endocrine therapy alone as adjuvant therapy. The primary lesion specimens obtained during surgery were analyzed using the 95GC breast cancer multigene assay. Based on the 95GC results, patients were classified into low-risk (95GC-L) and high-risk (95GC-H) groups.

Results

The 10-year relapse-free survival rates were 88.4 and 59.6% for the 95GC-L and 95GC-H groups, respectively. Histologic grade, Ki-67, and PAM50 exhibited a significant relationship with the 95GC results. The segregation into 95GC-L and 95GC-H groups within established clinical factors can identify subgroups of patients using histologic grade or PAM50 classification with good prognosis without receiving chemotherapy.

Conclusions

Based on the results of our retrospective study, 95GC could be used to evaluate the long-term prognosis of ER-positive, node-negative breast cancer. Even though further prospective validation is necessary, the inclusion of 95GC in clinical practice could help to select optimal treatments for breast cancer patients and identify those who do not benefit from the addition of chemotherapy, thus avoiding unnecessary treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08778-5.

A 95-gene signature stratifies recurrence risk of invasive disease in ER-positive, HER2-negative, node-negative breast cancer with intermediate 21-gene signature recurrence scores

PURPOSE

A subset of patients with intermediate 21-gene signature assay recurrence score may benefit from adjuvant chemoendocrine therapy, but a predictive strategy is needed to identify such patients. The 95-gene signature assay was tested to stratify patients with intermediate RS into high (95GC-H) and low (95GC-L) groups that were associated with invasive recurrence risk.

METHODS

Patients with ER-positive, HER2-negative, node-negative breast cancer and RS 11-25 who underwent definitive surgery and adjuvant endocrine therapy without any cytotoxic agents were included. RNA was extracted from archived formalin-fixed, paraffin-embedded samples, and 95-gene signature was calculated.

RESULTS

206 patients had RS of 11-25 (95GC-L, N = 163; 95GC-H, N = 43). In Cox proportional hazards model, 95GC-H was significantly associated with shorter time to recurrence than was 95GC-L (HR 5.94; 95%CI 1.81-19.53; P = 0.005). The correlation between 95-gene signature and 21-gene signature assay scores was not strong (correlation coefficient r = 0.27), which might suggest that 95-gene signature reflects biological characteristics differing from what 21-gene signature shows.

CONCLUSIONS

The 95-gene signature stratifies patients with ER-positive, HER2-negative, node-negative invasive breast cancer and intermediate RS of 11-25 into high and low groups that are associated with recurrence risk of invasive disease. Further retrospective analysis in the prospectively accrued TAILORx population is warranted to confirm that 95-gene signature can identify patients who would benefit from adjuvant chemoendocrine therapy.

The multigene classifiers 95GC/42GC/155GC for precision medicine in ER-positive HER2-negative early breast cancer

In clinical decision‐making, to decide the indication for adjuvant chemotherapy for estrogen receptor‐positive (ER+), human epidermal growth factor receptor‐2‐negative (HER2−), and node‐negative (n0) breast cancer patients, the accurate estimation of recurrence risk is essential. Unfortunately, conventional prognostic factors, such as tumor size, histological grade and ER, progesterone receptor (PR), and HER2 status as well as Ki67 index, are not sufficiently accurate for such estimation. Therefore, several multigene assays (MGAs) based on the mRNA expression analysis of multiple genes in tumor tissue have been developed to better predict patient prognosis. These assays include Oncotype DX, MammaPrint, PAM50, GGI, EndoPredict, and BCI. We developed Curebest™ 95‐Gene Classifier Breast (95GC) classifier, which is unique in that mRNA expression data of all 20 000 human genes are secondarily obtainable, as the 95GC assay is performed using Affymetrix microarray. This can capture mRNA expression of not only 95 genes but also every gene at once, and such gene expression data can be utilized by the other MGAs that we have developed, such as the 155GC, which is used for the prognostic prediction of ER+/HER2− breast cancer patients treated with neoadjuvant chemotherapy. We also developed the 42GC for predicting late recurrence in ER+/HER2− breast cancer patients. In this mini‐review, our recent attempt at the development of various MGAs, which is expected to facilitate the implementation of precision medicine in ER+/HER2− breast cancer patients, is presented with a special emphasis on 95GC.

Tumour profiling tests to guide adjuvant chemotherapy decisions in early breast cancer: a systematic review and economic analysis

BACKGROUND

Breast cancer and its treatment can have an impact on health-related quality of life and survival. Tumour profiling tests aim to identify whether or not women need chemotherapy owing to their risk of relapse.

OBJECTIVES

To conduct a systematic review of the effectiveness and cost-effectiveness of the tumour profiling tests oncotype DX^® (Genomic Health, Inc., Redwood City, CA, USA), MammaPrint^® (Agendia, Inc., Amsterdam, the Netherlands), Prosigna^® (NanoString Technologies, Inc., Seattle, WA, USA), EndoPredict^® (Myriad Genetics Ltd, London, UK) and immunohistochemistry 4 (IHC4). To develop a health economic model to assess the cost-effectiveness of these tests compared with clinical tools to guide the use of adjuvant chemotherapy in early-stage breast cancer from the perspective of the NHS and Personal Social Services.

DESIGN

A systematic review and health economic analysis were conducted.

REVIEW METHODS

The systematic review was partially an update of a 2013 review. Nine databases were searched in February 2017. The review included studies assessing clinical effectiveness in people with oestrogen receptor-positive, human epidermal growth factor receptor 2-negative, stage I or II cancer with zero to three positive lymph nodes. The economic analysis included a review of existing analyses and the development of a de novo model.

RESULTS

A total of 153 studies were identified. Only one completed randomised controlled trial (RCT) using a tumour profiling test in clinical practice was identified: Microarray In Node-negative Disease may Avoid ChemoTherapy (MINDACT) for MammaPrint. Other studies suggest that all the tests can provide information on the risk of relapse; however, results were more varied in lymph node-positive (LN+) patients than in lymph node-negative (LN0) patients. There is limited and varying evidence that oncotype DX and MammaPrint can predict benefit from chemotherapy. The net change in the percentage of patients with a chemotherapy recommendation or decision pre/post test ranged from an increase of 1% to a decrease of 23% among UK studies and a decrease of 0% to 64% across European studies. The health economic analysis suggests that the incremental cost-effectiveness ratios for the tests versus current practice are broadly favourable for the following scenarios: (1) oncotype DX, for the LN0 subgroup with a Nottingham Prognostic Index (NPI) of > 3.4 and the one to three positive lymph nodes (LN1-3) subgroup (if a predictive benefit is assumed); (2) IHC4 plus clinical factors (IHC4+C), for all patient subgroups; (3) Prosigna, for the LN0 subgroup with a NPI of > 3.4 and the LN1-3 subgroup; (4) EndoPredict Clinical, for the LN1-3 subgroup only; and (5) MammaPrint, for no subgroups.

LIMITATIONS

There was only one completed RCT using a tumour profiling test in clinical practice. Except for oncotype DX in the LN0 group with a NPI score of > 3.4 (clinical intermediate risk), evidence surrounding pre- and post-test chemotherapy probabilities is subject to considerable uncertainty. There is uncertainty regarding whether or not oncotype DX and MammaPrint are predictive of chemotherapy benefit. The MammaPrint analysis uses a different data source to the other four tests. The Translational substudy of the Arimidex, Tamoxifen, Alone or in Combination (TransATAC) study (used in the economic modelling) has a number of limitations.

CONCLUSIONS

The review suggests that all the tests can provide prognostic information on the risk of relapse; results were more varied in LN+ patients than in LN0 patients. There is limited and varying evidence that oncotype DX and MammaPrint are predictive of chemotherapy benefit. Health economic analyses indicate that some tests may have a favourable cost-effectiveness profile for certain patient subgroups; all estimates are subject to uncertainty. More evidence is needed on the prediction of chemotherapy benefit, long-term impacts and changes in UK pre-/post-chemotherapy decisions.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42017059561.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Adjuvant and neoadjuvant therapy for breast cancer

Systemic therapies for operable breast cancer patients have improved outcomes and have thus become standard treatments. Recently, new molecular target drugs and regimens are being developed based on the predicted sensitivity for specific breast cancer histological types. Systemic therapy is selected according to recurrence risk, with the treatment for low-risk patients being de-escalated, while high-risk patients receive aggressive systemic treatment with an adequate dose and duration. Neoadjuvant systemic therapy has a different aim. The efficacy of systemic therapies, based on the sensitivities to drugs, is supported by improvements in the rate of breast-conserving therapy. The response to neoadjuvant systemic therapy is the most important factor for predicting outcomes and selecting the optimal adjuvant therapy. Novel biological markers unique to individual patients allow appropriate targeted therapy, which can achieve optimal efficacy.

Radiogenomics of magnetic resonance imaging and a new multi-gene classifier for predicting recurrence prognosis in estrogen receptor-positive breast cancer: A preliminary study

To examine the correlation of qualitative and quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) results with 95-gene classifier or Curebest 95-gene classifier Breast (95GC) results for recurrence prediction in estrogen receptor-positive breast cancer (ERPBC).This retrospective study included 78 ERPBC patients (age range, 24-74 years) classified into high- (n = 33) and low- (n = 45) risk groups for recurrence based on 95GC and who underwent DCE-MRI between July 2006 and November 2012. For qualitative evaluation, mass shape, margin, and internal enhancement based on BI-RADS MRI lexicon and multiplicity were determined by consensus interpretation by 2 breast radiologists. For quantitative evaluation, mass size, volume ratios of the DCE-MRI kinetics, and both the kurtosis and the skewness of the intensity histogram for the whole mass in the initial and delayed phases were determined. Differences between the 2 risk-groups were analyzed using univariate logistic regression analyses and multiple logistic regression analyses. Receiver-operating characteristic curve cut-off values were used to define the groups.As for the qualitative findings, the difference between the 2 groups was not significant. For the quantitative data, the volume ratio of "medium" in the initial phase differed significantly between the 2 groups (P = .049). The volume ratio of "medium" (P = .006) and of "slow-persistent" (P = .005), and the delayed phase kurtosis (P = .012) in the univariate logistic regression analyses, and in the multiple logistic regression, volume ratio of "medium" >38.9% and delayed phase kurtosis >3.31 were identified as significant high-risk indicators (odds ratio, 5.83 and 3.55; 95% confidence interval, 1.58 to 21.42 and 1.24 to 10.15; P = .008 and P = .018, respectively).A high volume ratio of "medium" in the initial phase and/or high kurtosis in the delayed phase for quantitative evaluation could predict high ERPBC recurrence risk based on 95GC.

Decision of Adjuvant Systemic Treatment in HR+ HER2- Early Invasive Breast Cancer: Which Biomarkers Could Help?

The decision to administer adjuvant chemotherapy in treatment of early invasive breast cancer (EBC) is often complex, particularly for hormone receptor-positive (HR+) diseases, and current guidelines often classify these patients in an intermediate-risk group. Several biomarkers are currently available in this indication, in order to obtain additional and more accurate prognostic information compared to classic clinicopathological characteristics and guide the indication of adjuvant chemotherapy, optimizing the efficacy/toxicity ratio. We conducted a systematic review to evaluate the clinical validity and clinical utility of five biomarkers (uPA/PAI-1, OncotypeDX^®, MammaPrint^®, PAM50, and EndoPredict^®) in HR+/HER2- EBC, whatever the nodal status. A total of 89 studies met the inclusion criteria. Even though data currently available confirm the clinical validity of these biomarkers, there is a lack of data regarding clinical utility for most of them. Prospective studies in well-defined populations are needed to integrate these biomarkers in a decision strategy.

Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients

PURPOSE

Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence.

METHODS

For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0).

RESULTS

With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence.

CONCLUSION

We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.

Systematic review of the clinical and economic value of gene expression profiles for invasive early breast cancer available in Europe

Gene expression profiles with prognostic capacities have shown good performance in multiple clinical trials. However, with multiple assays available and numerous types of validation studies performed, the added value for daily clinical practice is still unclear. In Europe, the MammaPrint, OncotypeDX, PAM50/Prosigna and Endopredict assays are commercially available. In this systematic review, we aim to assess these assays on four important criteria: Assay development and methodology, clinical validation, clinical utility and economic value. We performed a literature search covering PubMed, Embase, Web of Science and Cochrane, for studies related to one or more of the four selected assays. We identified 147 papers for inclusion in this review. MammaPrint and OncotypeDX both have evidence available, including level IA clinical trial results for both assays. Both assays provide prognostic information. Predictive value has only been shown for OncotypeDX. In the clinical utility studies, a higher reduction in chemotherapy was achieved by OncotypeDX, although the number of available studies differ considerably between tests. On average, economic evaluations estimate that genomic testing results in a moderate increase in total costs, but that these costs are acceptable in relation to the expected improved patient outcome. PAM50/prosigna and EndoPredict showed comparable prognostic capacities, but with less economical and clinical utility studies. Furthermore, for these assays no level IA trial data are available yet. In summary, all assays have shown excellent prognostic capacities. The differences in the quantity and quality of evidence are discussed. Future studies shall focus on the selection of appropriate subgroups for testing and long-term outcome of validation trials, in order to determine the place of these assays in daily clinical practice.

Endocrine sensitivity of estrogen receptor-positive breast cancer is negatively correlated with aspartate-β-hydroxylase expression

Although prognostic markers for early estrogen receptor (ER)‐positive breast cancer have been extensively developed, predictive markers for adjuvant endocrine therapy are still lacking. Focusing on the mechanisms underlying endocrine resistance, we investigated whether the endocrine sensitivity of ER‐positive breast cancer cells was correlated with the expression of aspartate‐β‐hydroxylase (ASPH), which is involved in the development of hepatocellular carcinoma. ASPH expression in ER‐positive and tamoxifen‐resistant breast cancer cells was upregulated by the MAPK and phosphoinositide‐3 kinase (PI3K) pathways, which both play pivotal roles in endocrine resistance. In the clinical setting, ASPH expression was negatively correlated with recurrence‐free survival of luminal B breast cancer patients that received adjuvant endocrine therapy, but not in patients that did not receive adjuvant endocrine therapy. Luminal B breast cancer is one of the intrinsic molecular subtypes identified by the Prediction Analysis of Microarray 50 (PAM50) multiple gene classifier, and because of its poor response to endocrine therapy, chemotherapy in addition to endocrine therapy is generally required after surgical resection. Our results suggest that the endocrine sensitivity of luminal B breast cancer can be assessed by examining ASPH expression, which promotes the consideration of a prospective study on the association between ASPH expression at the mRNA and protein levels in luminal B breast cancer and subsequent response to endocrine therapy.

Novel rapid-immunohistochemistry using an alternating current electric field for intraoperative diagnosis of sentinel lymph nodes in breast cancer

Axillary lymph node status and pathological diagnosis of sentinel lymph nodes (SLNs) is a prognostic factor that influences management of postoperative therapy. Recent reports indicate that one-step nucleic acid amplification and hematoxylin and eosin (HE)-stained frozen sections are effective for intraoperative diagnosis of SLNs. In the present study, we report a rapid-immunohistochemical staining (R-IHC) method that enables intraoperative detection of SLN metastases within 16 min using an anti-cytokeratin antibody. This is the first report on SLN diagnosis using R-IHC in patients with breast cancer. We prospectively examined 160 dissected SLNs from 108 breast cancer patients who underwent surgery at our institute. The dissected SLNs were sectioned and conventionally stained with HE or immunohistochemically labeled with anti-cytokeratin antibody using R-IHC procedures. Intraoperative R-IHC analyses were completed within 16 min, after which diagnoses were made by two pathologists. The total time required for intraoperative diagnosis was about 20 min. In this study series, R-IHC detected four metastatic SLNs that were undetected using conventional HE staining (4/20, 20.0%). Compared with subsequent permanent diagnosis, R-IHC offered 95.2% sensitivity and 100% specificity. These findings indicate R-IHC is a clinically applicable technique that enables precise and quick intraoperative detection of micro- and macrometastasis in breast cancer.

The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures

BACKGROUND

Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease.

METHODS

Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors.

RESULTS

The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease.

CONCLUSIONS

We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we present candidate biological processes, unique to LN- and LN+ disease, that may indicate risk of relapse.

Multi-gene classifiers for prediction of recurrence in breast cancer patients

Accurate prediction of recurrence risk is of vital importance for tailoring adjuvant chemotherapy for individual breast cancer patients. Although recurrence risk has been assessed by means of examination of histological data and biomarkers (ER, PR, HER2, Ki67), such conventional examinations are not accurate enough to select subsets of patients who are at sufficiently low risk of recurrence to be spared adjuvant chemotherapy without comprising the prognosis. In the past two decades or so, comprehensive gene expression analysis technology has rapidly developed and made it possible to construct recurrence prediction models for breast cancer based on multi-gene expression in tumor tissues. These models include MammaPrint, Oncotype DX, PAM50 ROR, GGI, EndoPredict, BCI, and Curebest 95GC. In clinical practice, these multi-gene classifiers are mostly used for ER-positive and node-negative breast cancer patients for whom deciding the indication of adjuvant chemotherapy based on conventional histological examination findings alone is often difficult. This article briefly reviews these multi-gene expression-based classifiers with special emphasis on Curebest™ 95GC, which was developed by us for ER-positive and node-negative breast cancer patients.

Gene expression-based prognostic and predictive tools in breast cancer

Genomic assays measuring the expression of multiple genes have made their way into clinical practice and their utilization is now recommended by major international guidelines. A basic property of these tests is their capability to sub-divide patients into high- and low-risk cohorts thereby providing prognostic, and in certain settings, predictive decision support. Here, we summarize commercially available assays for breast cancer including RT-PCR and gene chip-based tests. Given the relative uncertainty in cancer treatment, multigene tests have the potential for a significant cost reduction as they can pinpoint those patients for whom chemotherapy proves to be unnecessary. However, concordance of risk assessment for an individual patient is still far from optimal. Additionally, emerging multigene approaches focus on predicting therapy response, which is a black spot of current tests. Promising techniques include the homologous recombination deficiency score, utilization of massive parallel sequencing to identify driver genes, employment of internet-based meta-analysis tools and investigation of miRNA expression signatures. Combination of multiple simultaneous analyses at diagnosis, including classical histopathological diagnostics, monogenic markers, genomic signatures and clinical parameters will most likely bring maximal benefit for patients. As the main driving force behind such genomic tests is the power to achieve cost reduction due to avoiding unnecessary systemic treatment, the future is most likely to hold a further proliferation of such assays.