Predicting response to primary chemotherapy: gene expression profiling of paraffin-embedded core biopsy tissue

Artificial intelligence in digital histopathology for predicting patient prognosis and treatment efficacy in breast cancer

INTRODUCTION

Histological images contain phenotypic information predictive of patient outcomes. Due to the heavy workload of pathologists, the time-consuming nature of quantitatively assessing histological features, and human eye limitations to recognize spatial patterns, manually extracting prognostic information in routine pathological workflows remains challenging. Digital pathology has facilitated the mining and quantification of these features utilizing whole-slide image (WSI) scanners and artificial intelligence (AI) algorithms. AI algorithms to identify image-based biomarkers from the tumor microenvironment (TME) have the potential to revolutionize the field of oncology, reducing delays between diagnosis and prognosis determination, allowing for rapid stratification of patients and prescription of optimal treatment regimes, thereby improving patient outcomes.

AREAS COVERED

In this review, the authors discuss how AI algorithms and digital pathology can predict breast cancer patient prognosis and treatment outcomes using image-based biomarkers, along with the challenges of adopting this technology in clinical settings.

EXPERT OPINION

The integration of AI and digital pathology presents significant potential for analyzing the TME and its diagnostic, prognostic, and predictive value in breast cancer patients. Widespread clinical adoption of AI faces ethical, regulatory, and technical challenges, although prospective trials may offer reassurance and promote uptake, ultimately improving patient outcomes by reducing diagnosis-to-prognosis delivery delays.

Unveiling the HER2-low phenomenon: exploring immunohistochemistry and gene expression to characterise HR-positive HER2-negative early breast cancer

PURPOSE

HER2-low breast cancer (BC) is a novel entity with relevant therapeutic implications, especially in hormone receptor (HR) positive BC. This study examines whether HER2 mRNA through the 21-gene assay, Oncotype DX (ODX), can refine the diagnosis of HER2-low and HER2-zero, obtained by immunohistochemistry (IHC).

METHODS

Between Jan 2021 and Jan 2023, 229 consecutive HR-positive HER2-negative early BC (T1-3 N0-1) have been characterised by IHC and ODX. HER2 status by IHC was either zero (IHC-0) or low (IHC-1 + and IHC-2 + /ISH-negative) while HER2-zero was further divided into HER2-null (IHC-0) and HER2-ultralow (IHC-1-10%). HER2 gene expression by ODX was negative if lower 10.7.

RESULTS

The distribution of HER2 IHC was as follows: 53.3% HER2-0, 29.25% HER2-1 + , and 17.5% HER2-2 + . The clinicopathological characteristics were similar in the three groups, with higher PgR-negative rate in HER2-zero (13.9% vs 3% vs 5%). The distribution of RS was homogeneous in the three groups with the median HER2 gene expression of 9.20 [IQR: 8.70-9.60]. HER2 gene expression gradually increased as the IHC score, with substantial overlap. After adjusting for confounders, HER2-1 + and HER2 2 + had a significant positive correlation between HER2 gene expression and IHC [OR 1.42, 95% CI 1.21 to 1.68, p < 0.001; OR 1.96, 95% CI 1.61 to 2.37, p < 0.001] compared to the HER2-zero group. HER2 gene expression did not differ between HER2-null and HER2-ultralow subgroups.

CONCLUSION

Due to the substantial overlap, the HER2 gene expression is unable to properly distinguish HER2-low and HER2-zero IHC whose accurate identification is critical in the context of HER2-negative BC.

Multigene profiles to guide the use of neoadjuvant chemotherapy for breast cancer: a Copenhagen Breast Cancer Genomics Study

Estrogen receptor (ER) and human epidermal growth factor 2 (HER2) expression guide the use of neoadjuvant chemotherapy (NACT) in patients with early breast cancer. We evaluate the independent predictive value of adding a multigene profile (CIT256 and PAM50) to immunohistochemical (IHC) profile regarding pathological complete response (pCR) and conversion of positive to negative axillary lymph node status. The cohort includes 458 patients who had genomic profiling performed as standard of care. Using logistic regression, higher pCR and node conversion rates among patients with Non-luminal subtypes are shown, and importantly the predictive value is independent of IHC profile. In patients with ER-positive and HER2-negative breast cancer an odds ratio of 9.78 (95% CI 2.60;36.8), P < 0.001 is found for pCR among CIT256 Non-luminal vs. Luminal subtypes. The results suggest a role for integrated use of up-front multigene subtyping for selection of a neoadjuvant approach in ER-positive HER2-negative breast cancer.

Optimal treatment strategy for hormone receptor-positive human epidermal growth factor receptor 2-negative breast cancer patients with 1-2 suspicious axillary lymph node metastases on breast magnetic resonance imaging: upfront surgery vs. neoadjuvant chemotherapy

Background

It is unclear whether upfront surgery or neoadjuvant chemotherapy is appropriate for first treatment in hormone receptor (HR)-positive human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients with 1-2 suspicious axillary lymph node (ALN) metastases on preoperative breast magnetic resonance imaging (MRI).

Method

We identified 282 patients with HR+HER2- breast cancer and 1-2 suspicious ALN metastases on baseline breast MRI (147 received upfront surgery; 135 received neoadjuvant chemotherapy). We evaluated the predictive clinicopathological factors for pN2-3 in the adjuvant setting and axillary pathologic complete response (pCR) in the neoadjuvant setting.

Results

Lymphovascular invasion (LVI)-positive and clinical tumors >3 cm were significantly associated with pN2-3 in patients who received upfront surgery. The pN2-3 rate was 9.3% in patients with a clinical tumor ≤ 3 cm and LVI-negative versus 34.7% in the others (p < 0.001). The pN2-3 rate in patients with a clinical tumor ≤ 3 cm and LVI-negative and in the others were 9.3% versus 34.7% in all patients (p < 0.001), 10.7% versus 40.0% (p = 0.033) in patients aged < 50 years, and 8.5% versus 31.0% in patients aged ≥ 50 years (p < 0.001), respectively. In the neoadjuvant setting, patients with tumor-infiltrating lymphocytes (TILs) ≥ 20% had a higher axillary pCR than those with TILs < 20% (46.7% vs. 15.3%, p < 0.001). A similar significant finding was also observed in patients < 50 years.

Conclusions

Upfront surgery may be preferable for patients aged ≥ 50 years with a clinical tumor < 3 cm and LVI-negative, while neoadjuvant chemotherapy may be preferable for those aged < 50 years with TILs ≥ 20%.

Gene-expression signatures to inform neoadjuvant treatment decision in HR+/HER2- breast cancer: Available evidence and clinical implications

Over the last few years, the indication for chemotherapy use in HR+/HER2- early BC has been significantly modified by the introduction of gene-expression profiling. In the adjuvant setting, several gene-expression signatures have been validated to discriminate early stage HR+/HER2- BC with different prognosis and to identify patients for which adjuvant chemotherapy can be spared. Considering their ability to optimize the choice of adjuvant treatment and the increasing use of neoadjuvant approach in early BC, the potential use of gene-expression signatures to discriminate patients to be candidate to neoadjuvant chemotherapy or endocrine treatment appears particularly appealing. Indeed, the San Gallen Consensus Conference panel recently endorsed the use of genomic assays on core biopsies as a potential strategy for choosing the type of neoadjuvant treatment (chemotherapy or endocrine therapy) in selected patients. In this context, we here review evidence supporting the use of most common commercially available gene-expression signatures (Oncotype DX, MammaPrint, PAM50, EndoPredict and Breast Cancer Index) in patients receiving neoadjuvant therapy for HR+/HER2- BC. Data on the association of gene expression signatures and response to neoadjuvant chemotherapy or neoadjuvant endocrine therapy will be reviewed and the clinical implications of this data to guide the clinical decision-making process in early HR+/HER2- BC will be discussed.

Palpable Adenopathy Does Not Indicate High-Volume Axillary Nodal Disease in Hormone Receptor-Positive Breast Cancer

BACKGROUND

Axillary metastases in the form of palpable adenopathy indicate the need for neoadjuvant chemotherapy or axillary lymph node dissection (ALND). Patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) disease infrequently have nodal pathologic complete response to neoadjuvant chemotherapy and often require ALND. Sentinel lymph node biopsy is an accepted treatment for patients with two or fewer non-palpable nodal metastases who are undergoing breast conservation. The proportion of patients with HR+/HER2- disease with palpable adenopathy and two or fewer nodal metastases is unknown.

METHODS

Patients with cT1-T3N1 HR+/HER2- disease with palpable adenopathy were identified from a prospective database. Patients who underwent mastectomy or breast-conserving therapy with ALND were included in this study, whereas patients who received neoadjuvant chemotherapy were excluded. Clinicopathologic characteristics were compared between patients with two or fewer or more than two positive nodes on ALND.

RESULTS

Of 180 patients included, 78 (43%) had two or fewer positive nodes on ALND, including 40/72 patients (56%) who underwent lumpectomy. On univariate analysis, cT1 tumor, unifocal tumor, only one palpable node, and two or fewer suspicious nodes on ultrasound were associated with two or fewer positive nodes on ALND. On multivariable analysis, number of suspicious nodes on ultrasound and cT stage were independently associated with two or fewer positive nodes on ALND.

CONCLUSIONS

A substantial minority of patients with cT1-3N1 HR+/HER2- disease with palpable adenopathy had two or fewer positive nodes on ALND. Standard clinicopathologic features and ultrasound findings can help identify candidates for upfront sentinel lymph node biopsy as a strategy to avoid ALND. Prospective studies evaluating this approach are warranted.

Is oestrogen receptor-negative/progesterone receptor-positive (ER-/PR+) a real pathological entity?

Background

The existence of oestrogen receptor-negative (ER−)/progesterone receptor-positive (PR+) breast cancer continues to be an area of controversy amongst oncologists and pathologists.

Methods

To re-evaluate breast cancers originally classified as ER−/PR+ via Oncotype DX® assay and compare molecular phenotype with Recurrence Score® (RS) result, clinicopathologic features and clinical outcomes were retrospectively obtained from electronic health records between January 1998 and June 2005. Archived formalin-fixed, paraffin-embedded (FFPE) tumour specimens were tested for the expression of ER, PR and human-epidermal-growth-factor-2. The number of positive ER−/PR+ samples confirmed by transcriptional analysis was the primary outcome of interest with event-free and overall survival as secondary outcomes. Biopsies from 26 patients underwent Oncotype DX testing and analysis.

Results

Approximately 60% were middle-aged (40–50 years old) women, and 84.6% had invasive ductal carcinoma. Based on the Oncotype DX assay, approximately 65% (N = 17) had ER+/PR+ status; 23% (N = 6) had ER−/PR− status; and 12% had a single hormone positive receptor (1 ER–/PR+, 2 ER+/PR–) status. Almost one-quarter of patients were stratified into the low-RS (<18) or intermediate-RS (18–30) results, and half of the patients had a high-RS (>30) result.

Conclusion

Our findings suggest the ER−/PR+ subtype is not a reproducible entity and emphasises the value of retesting this subtype via molecular methods for appropriate treatment selection and patient outcomes. Multigene assay analysis may serve as a second-line or confirming tool for clinical determination of ER/PR phenotype in breast cancer patients for targeted therapies.

Value of a 21-gene expression assay on core biopsy to predict neoadjuvant chemotherapy response in breast cancer: systematic review and meta-analysis

BACKGROUND

A recurrence score based on a 21-gene expression assay predicts the benefit of adjuvant chemotherapy in oestrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer. This systematic review aimed to determine whether the 21-gene expression assay performed on core biopsy at diagnosis predicted pathological complete response (pCR) to neoadjuvant chemotherapy.

METHODS

The study was performed according to PRISMA guidelines. Relevant databases were searched to identify studies assessing the value of the 21-gene expression assay recurrence score in predicting response to neoadjuvant chemotherapy in patients with breast cancer. The Newcastle-Ottawa Scale was used to assess the quality of the studies. Results are reported as risk ratio (RR) with 95 per cent confidence interval using the Cochrane-Mantel-Haenszel method for meta-analysis. Sensitivity analyses were carried out where appropriate.

RESULTS

Seven studies involving 1744 patients reported the correlation between pretreatment recurrence score and pCR. Of these, 777 patients (44.6 per cent) had a high recurrence score and 967 (55.4 per cent) a low-intermediate score. A pCR was achieved in 94 patients (5.4 per cent). The pCR rate was significantly higher in the group with a high recurrence score than in the group with a low-intermediate score (10.9 versus 1.1 per cent; RR 4.47, 95 per cent c.i. 2.76 to 7.21; P < 0.001). A significant risk difference was observed between the two groups (risk difference 0.10, 0.04 to 0.15; P = 0.001).

CONCLUSION

A high recurrence score is associated with higher pCR rates and a low-intermediate recurrence score may indicate chemoresistance. Routine assessment of recurrence score by the 21-gene expression assay on core biopsy might be of value when considering neoadjuvant chemotherapy in patients with ER-positive, HER2-negative breast cancer.

The Correlation of Magee EquationsTM and Oncotype DX® Recurrence Score From Core Needle Biopsy Tissues in Predicting Response to Neoadjuvant Chemotherapy in ER+ and HER2- Breast Cancer

Objective

Oncotype DX^® recurrence score (RS) can be predicted from Magee Equations^TM (MS) postoperatively. The aim of this study is to investigate correlation of MS with RS from pretreatment core needle biopsy (CNB) tissues, and their clinical usefulness in prediction of response to neoadjuvant chemotherapy (NCT) in estrogen receptor-positive and human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancer (BC).

Materials and Methods

Pretreatment CNB tissue samples from 60 patients with ER+/HER2- invasive BC were analyzed for MS and RS correlation. MS and RS were categorized as follows: low (<18), intermediate (18-30), and high (≥ 31). Percentage Tumor size Reduction (%TR) was used to assess tumor response to NCT, and substantial %TR was defined as at least 50% reduction (≥50%TR). Correlation between MS and RS, and predictive factors for the ≥50%TR achievement were assessed.

Results

MS and RS represented a strong correlation (Spearman's correlation; r=0.58, p<0.0001) as a continuous variable. As a categorical variable, the concordance between MS and RS was 43.3%, and it increased to 80% (r=0.61, p=0.003) with the exclusion of the intermediate risk categories. Although, there was pathologic complete response (pCR), MS showed the highest predictive power for the ≥50% TR achievement, none of the factors were statistically significant (p≥0.07).

Conclusion

Our study demonstrated that there was a strong correlation between MS and RS from pretreatment biopsy tissue samples in ER+ and HER2- invasive BC.

Oncotype DX Breast Cancer recurrence score resists inter-assay reproducibility with RT2-Profiler Multiplex RT-PCR

The Oncotype Dx assay is frequently used to test if breast cancer patients can be spared from chemotherapy without negative effects for their future clinical course. However, due to conflicting data on the assay utility, in the recent past its reimbursement situation in Germany was revised; due to continued requests by clinicians for predictive values, our group decided to implement an Oncotype Dx like alternative assay with the objective of obtaining quality and cost optimization. Customized RT²-Profiler assays covering the 21 gene panel of the Oncotype Dx assay were applied to a pilot cohort of breast cancer patients with known Oncotype Dx Recurrence Score (RS). The Ct values obtained with RT²-Profiler-assays were used to calculate the unscaled Recurrence Score (RSu) values and the thereon based RS according to the Oncotype DX assay rules if available. Despite consistent assay performance it was impossible to establish correlations between RT²-Profiler recurrence scores with the respective Oncotype DX values not to mention exact matches. By following the Oncotype DX assay and its interpretation as close as possible we faced several obstructions such as lack of information on RNA amount used, missing units in the single gene expression report, missing references cited in the original study that should explain the determination of the recurrence score formula, and vague information on the normalization of the gene expression impeding the reproduction of Oncotype Dx results in other laboratories. Unfortunately, the Oncotype Dx assay cannot be confirmed by the customized RT²-profiler assay, not least because of the fact that the individual gene measurements are not provided in the medical report, although these are mandatory for the RS calculation. In fact, the "single gene report" only contains unscaled scores of the ER, PR, and Her2 genes without any internationally accepted unit used to describe a transcript quantity. Therefore a direct comparison with the in-house measurement to evaluate its performance is impossible. With regard to our findings and the fact that the Oncotype RS represents a likelihood of the risk of relapse it thus remains impossible to assess the clinical necessity of this assay.

EarlyR signature predicts response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

EarlyR gene signature uses ESPL1, SPAG5, MKI67, PLK1 and PGR to classify ER+ breast cancer (ER+ BC) into EarlyR-Low, EarlyR-Int, and EarlyR-High risk strata and is prognostic in patients treated with adjuvant chemotherapy. The ability of EarlyR to predict pathological complete response (pCR) and long-term survival following neoadjuvant chemotherapy (NACT) is evaluated herein.

MATERIALS

The ability of EarlyR gene signature to predict pCR was assessed in publicly available Affymetrix microarray datasets (Cohort A; n = 659; 74 pCR events) derived from NACT-treated ER+ BC patients. Distant relapse-free survival (DRFS) results were analyzed in patients treated with NACT and adjuvant hormone therapy (AHT) (n = 281) and compared with patients treated with AHT alone (n = 455) (Cohort B; n = 736; 142 events).

RESULTS

In cohort A, EarlyR was a significant predictor of pCR (p = 5.8 × 10-11) (EarlyR-Low, n = 400, pCR = 40, 5%; EarlyR-Int, n = 69, pCR = 7, 15% and EarlyR-High, n = 190, pCR = 47, 24%). In EarlyR-Low of Cohort B, the 5-year DRFS was not significantly (p = 0.55) different between NACT + AHT [0.81 (95%CI 0.73-0.90)] and AHT-only [0.85 (95%CI 0.81-0.90)]. In contrast, in EarlyR-High, the 5-year DRFS was higher (p = 0.019) in NACT + AHT [0.81 (95%CI 0.70-0.93)] as compared to AHT-only [0.60 (95%CI 0.51-0.71)].

CONCLUSIONS

High EarlyR is strongly associated with pCR in patients treated with neoadjuvant chemotherapy. EarlyR also predicts poor DRFS outcomes for patients in EarlyR-High not receiving NACT, and improved survival in NACT-treated EarlyR-High patients. EarlyR is not only a prognostic assay but also a predictive assay that identifies patients, who are also likely to respond to chemotherapy.

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer

Background

Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. However, these tests are typically expensive, time consuming, and tissue-destructive.

Methods

In this paper, we evaluate the ability of computer-extracted nuclear morphology features from routine hematoxylin and eosin (H&E) stained images of 178 early stage ER+ breast cancer patients to predict corresponding risk categories derived using the Oncotype DX test. A total of 216 features corresponding to the nuclear shape and architecture categories from each of the pathologic images were extracted and four feature selection schemes: Ranksum, Principal Component Analysis with Variable Importance on Projection (PCA-VIP), Maximum-Relevance, Minimum Redundancy Mutual Information Difference (MRMR MID), and Maximum-Relevance, Minimum Redundancy - Mutual Information Quotient (MRMR MIQ), were employed to identify the most discriminating features. These features were employed to train 4 machine learning classifiers: Random Forest, Neural Network, Support Vector Machine, and Linear Discriminant Analysis, via 3-fold cross validation.

Results

The four sets of risk categories, and the top Area Under the receiver operating characteristic Curve (AUC) machine classifier performances were: 1) Low ODx and Low mBR grade vs. High ODx and High mBR grade (Low-Low vs. High-High) (AUC = 0.83), 2) Low ODx vs. High ODx (AUC = 0.72), 3) Low ODx vs. Intermediate and High ODx (AUC = 0.58), and 4) Low and Intermediate ODx vs. High ODx (AUC = 0.65). Trained models were tested independent validation set of 53 cases which comprised of Low and High ODx risk, and demonstrated per-patient accuracies ranging from 75 to 86%.

Conclusion

Our results suggest that computerized image analysis of digitized H&E pathology images of early stage ER+ breast cancer might be able predict the corresponding Oncotype DX risk categories.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4448-9) contains supplementary material, which is available to authorized users.

The impact of Oncotype DX® recurrence score of paraffin-embedded core biopsy tissues in predicting response to neoadjuvant chemotherapy in women with breast cancer

BACKGROUND

Oncotype DX® test is beneficial in predicting recurrence free survival in estrogen receptor positive (ER+) breast cancer. Ability of the assay to predict response to neoadjuvant chemotherapy (NCT) is less well-studied.

OBJECTIVE

We hypothesize a positive association between the Oncotype DX® recurrence score (RS) and the percentage tumor response (%TR) after NCT.

METHODS

Pre-therapy RS was measured on core biopsies from 60 patients with ER+, HER2- invasive breast cancer (IBC) who then received NCT. Pre-therapy tumor size was measured using imaging. %TR, partial response (PR; >50%), pathologic complete response (pCR) and breast conserving surgery (BCS) rates were measured.

RESULTS

Median RS was 20 (2-69). Median %TR was 42 (0-97)%. PR was observed in 43% of patients. There was no association between %TR and pre-NCT tumor size, age, Nottingham score or nodal status (p > 0.05). No statistically significant association with %TR was seen with RS as a categorical or continuous variable (p = 0.21 and 0.7, respectively). Response to NCT improved as ER (p = 0.02) by RT-PCR decreased. Lower ER expression by IHC correlated with response (p = 0.03).

CONCLUSIONS

In patients with ER+ IBC receiving NCT, RS did not predict response to NCT using %TR. The benefit of the assay prior to NCT requires further study.

How do women trade-off benefits and risks in chemotherapy treatment decisions based on gene expression profiling for early-stage breast cancer? A discrete choice experiment

OBJECTIVES

Gene expression profiling (GEP) of tumours informs baseline risk prediction, potentially affecting adjuvant chemotherapy decisions for women with early-stage breast cancer. Since only 15% will experience a recurrence, concerns have been raised about potential harms from overtreatment and high GEP costs in publicly funded healthcare systems. We aimed to estimate preferences and personal utility of GEP testing information and benefit-risk trade-offs in chemotherapy treatment decisions.

DESIGN, SETTING AND INTERVENTION

Based on literature review and findings from our qualitative research (focus groups, interviews with patients with breast cancer and medical oncologists), we developed a discrete choice experiment (DCE) survey and administered it via an internet panel. The DCE included 12 choice tasks with 5 attributes and 3 alternatives considering orthogonality, D-efficiency and level balance.

PARTICIPANTS

The DCE survey was administered to 1004 Canadian women from the general population.

MAIN OUTCOME MEASURES

Preferences were analysed using conditional logit and hierarchical Bayes and evaluated for goodness of fit. We conducted simulation analyses for alternative scenarios.

RESULTS

GEP test score indicating likely benefit from chemotherapy was the most important attribute. Doctor's clinical estimate of the risk of cancer returning, trust in your cancer doctor and side effects of chemotherapy (temporary and permanent) were relatively less important but showed significant differences among levels. In the scenario analyses, 78% were likely to choose chemotherapy in a high-risk scenario, 55% in a moderate-risk scenario and 33% in a low-risk scenario, with the other attributes held constant. A high GEP score was more important in influencing the choice of chemotherapy for those at intermediate clinical risk.

CONCLUSIONS

GEP testing information influences chemotherapy treatment decisions in early-stage breast cancer and varies depending on clinical risk. Clinicians should be aware of these differences and tailor the use of GEP testing accordingly.

The influence of gene expression profiling on decisional conflict in decision making for early-stage breast cancer chemotherapy

BACKGROUND

Women with early-stage breast cancer, of whom only 15% will experience a recurrence, are often conflicted or uncertain about taking chemotherapy. Gene expression profiling (GEP) of tumours informs risk prediction, potentially affecting treatment decisions. We examined whether receiving a GEP test score reduces decisional conflict in chemotherapy treatment decision making.

METHODS

A general population sample of 200 women completed the decisional conflict scale (DCS) at baseline (no GEP test score scenario) and after (scenario with GEP test score added) completing a discrete choice experiment survey for early-stage breast cancer chemotherapy. We scaled the 16-item DCS total scores and subscores from 0 to 100 and calculated means, standard deviations and change in scores, with significance (p < 0.05) based on matched pairs t-tests.

RESULTS

We identified five respondent subgroups based on preferred treatment option; almost 40% did not change their chemotherapy decision after receiving GEP testing information. Total score and all subscores (uncertainty, informed, values clarity, support, and effective decision) decreased significantly in the respondent subgroup who were unsure about taking chemotherapy initially but changed to no chemotherapy (n =33). In the subgroup of respondents (n = 25) who chose chemotherapy initially but changed to unsure, effective decision subscore increased significantly. In the overall sample, changes in total and all subscores were non-significant.

CONCLUSIONS

GEP testing adds value for women initially unsure about chemotherapy treatment with a decrease in decisional conflict. However, for women who are confident about their treatment decisions, GEP testing may not add value. Decisions to request GEP testing should be personalised based on patient preferences.

Relevance of progesterone receptor immunohistochemical staining to Oncotype DX recurrence score

OBJECTIVE/BACKGROUND

Progesterone-receptor negativity (PR-) is predictive of adverse outcomes in estrogen receptor-positive (ER+) breast cancer. The Oncotype DX assay provides risk stratification for hormone receptor-positive (HR+) invasive breast cancer; however, the association of PR status and Oncotype DX recurrence scores (RSs) is less clear.

METHODS

We designed an analysis to determine whether a significant difference exists in the RS for ER+/PR- tumors when compared with ER+/PR+ breast cancer. Three hundred and fifty patients with HR+ invasive breast cancer who underwent Oncotype DX testing at our institution from December 2006 to October 2013 were included. We also examined the concordance in the HR status reported by immunohistochemical (IHC) and reverse transcriptase-polymerase chain reaction (RT-PCR) analyses. The data were analyzed by analysis of variance, F test, t test, and chi-square tests. Multivariate linear regression was used to determine significant predictors of Oncotype DX RS.

RESULTS

A total of 301 patients had ER+/PR+ tumors and 47 patients had ER+/PR- tumors by IHC. PR- tumors had a significantly higher RS than PR+ tumors (24.7±8.53 vs. 17.3±7.38; p<.001), predicting a greater 10-year risk of distant recurrence. Multivariate linear regression showed PR status and tumor grade to be significant predictors of Oncotype DX RS (p<.0001). A total of 284 patients had HR status reported by Oncotype DX assay. Concordance between IHC and RT-PCR was 99.3% for ER and 88.7% for PR.

CONCLUSION

Our study shows that ER+/PR- breast cancer tumors are associated with a significantly higher Oncotype DX scores; this interprets into a higher risk of recurrence. Our data also show that the concordance between IHC and RT-PCR was 99.3% for ER and lower at 88.7% for PR.

The relationship between quantitative human epidermal growth factor receptor 2 gene expression by the 21-gene reverse transcriptase polymerase chain reaction assay and adjuvant trastuzumab benefit in Alliance N9831

Introduction

The N9831 trial demonstrated the efficacy of adjuvant trastuzumab for patients with human epidermal growth factor receptor 2 (HER2) locally positive tumors by protein or gene analysis. We used the 21-gene assay to examine the association of quantitative HER2 messenger RNA (mRNA) gene expression and benefit from trastuzumab.

Methods

N9831 tested the addition of trastuzumab to chemotherapy in stage I–III HER2-positive breast cancer. For two of the arms of the trial, doxorubicin and cyclophosphamide followed by paclitaxel (AC-T) and doxorubicin and cyclophosphamide followed by paclitaxel and trastuzumab concurrent chemotherapy-trastuzumab (AC-TH), recurrence score (RS) and HER2 mRNA expression were determined by the 21-gene assay (Oncotype DX®) (negative <10.7, equivocal 10.7 to <11.5, and positive ≥11.5 log₂ expression units). Cox regression was used to assess the association of HER2 expression with trastuzumab benefit in preventing distant recurrence.

Results

Median follow-up was 7.4 years. Of 1,940 total patients, 901 had consent and sufficient tissue. HER2 by reverse transcriptase polymerase chain reaction (RT-PCR) was negative in 130 (14 %), equivocal in 85 (9 %), and positive in 686 (76 %) patients. Concordance between HER2 assessments was 95 % for RT-PCR versus central immunohistochemistry (IHC) (>10 % positive cells = positive), 91 % for RT-PCR versus central fluorescence in situ hybridization (FISH) (≥2.0 = positive) and 94 % for central IHC versus central FISH. In the primary analysis, the association of HER2 expression by 21-gene assay with trastuzumab benefit was marginally nonsignificant (nonlinear p = 0.057). In hormone receptor-positive patients (local IHC) the association was significant (p = 0.002). The association was nonlinear with the greatest estimated benefit at lower and higher HER2 expression levels.

Conclusions

Concordance among HER2 assessments by central IHC, FISH, and RT-PCR were similar and high. Association of HER2 mRNA expression with trastuzumab benefit as measured by time to distant recurrence was nonsignificant. A consistent benefit of trastuzumab irrespective of mHER2 levels was observed in patients with either IHC-positive or FISH-positive tumors. Trend for benefit was observed also for the small groups of patients with negative results by any or all of the central assays.

Trial registration

Clinicaltrials.gov NCT00005970. Registered 5 July 2000.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-015-0643-7) contains supplementary material, which is available to authorized users.

Gene-Expression-Based Predictors for Breast Cancer

An important and often complicated management decision in early stage hormone receptor (HR)-positive breast cancer relates to the use of adjuvant systemic chemotherapy. Although traditional clinicopathologic markers exist, tremendous progress has been achieved in the field of predictive biomarkers and genomics with both prognostic and predictive capabilities to identify patients who will potentially benefit from additional therapy. The use of these genomic tests in the neoadjuvant setting is also being studied and may lead to these tests providing clinical benefit even earlier in the disease course. Landmark articles published in the last few years have expanded our knowledge of breast cancer genomics to an unprecedented level, and mutational analysis via next-generation sequencing methods allows the identification of molecular targets for novel targeted therapeutic agents and clinical trials testing efficacy of targeted therapies, such as PI3K inhibitors, in addition to endocrine therapy for HR-positive breast cancer, are ongoing. We provide an in-depth review on the role of gene expression-based predictors in early stage breast cancer and an overview of future directions, including next-generation sequencing. Over the coming years, we anticipate a significant increase in utilization of genomic-based predictors for individualized selection and duration of endocrine therapy with and without genotype-driven targeted therapy, and a major decrease in the use of chemotherapy, possibly even leading to a chemotherapy-free road for early stage HR-positive breast cancer.

Endocrine Resistance in Breast Cancer

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

Access to personalized medicine: factors influencing the use and value of gene expression profiling in breast cancer treatment

Genomic information is increasingly being used to personalize health care. One example is gene expression profiling (gep) tests, which estimate recurrence risk to inform chemotherapy decisions in breast cancer. Recently, gep tests were publicly funded in Ontario. We explored the perceived utility of gep tests, focusing on the factors influencing their use and value in treatment decision-making by patients and oncologists.

METHODS

We conducted interviews with oncologists (n = 14) and interviews and a focus group with early-stage breast cancer patients (n = 28) who underwent gep testing. Both groups were recruited through oncology clinics in Ontario. Data were analyzed using the content analysis and constant comparison techniques.

RESULTS

Narratives from patients and oncologists provided insights into various factors facilitating and restricting access to gep. First, oncologists are positioned as gatekeepers of gep, providing access in medically appropriate cases. However, varying perceptions of appropriateness led to perceived inequities in access and negative impacts on the doctor-patient relationship. Second, media attention facilitated patient awareness of gep, but also complicated gatekeeping. Third, the dedicated administration attached to gep was burdensome and led to long waits for results and also to increased patient anxiety and delayed treatment. Collectively, because of barriers to access, those factors inadvertently heightened the perceived value of gep for patients relative to other prognostic indicators.

CONCLUSIONS

Our study delineates the factors facilitating and restricting access to gep, and highlights the roles of media and organization of services in the perceived value and utilization of gep. The results identify a need for administrative changes and practice guidelines to support streamlined and standardized use of gep tests.

Adaptive designs for clinical trials assessing biomarker-guided treatment strategies

BACKGROUND

The Biomarker Strategy Design has been proposed for trials assessing the value of a biomarker in guiding treatment in oncology. In such trials, patients are randomised to either receive the standard chemotherapy treatment or a biomarker-directed treatment arm, in which biomarker status is used to guide treatment.

METHODS

Motivated by a current trial, we consider an adaptive design in which two biomarkers are assessed. The trial is conducted in two stages. In the first stage, patients in the biomarker-guided arm are assessed using a standard and an alternative cheaper biomarker, with the standard biomarker guiding treatment. An analysis comparing biomarker results is then used to choose the biomarker to use for the remainder of the trial. The new biomarker is used if the results for the two biomarkers are sufficiently similar.

RESULTS

We show that in practical situations the first-stage results can be used to adapt the trial without type I error rate inflation. We also show that there can be considerable cost gains with only a small loss in power in the case where the alternative biomarker is highly concordant with the standard one.

CONCLUSIONS

Adaptive designs have an important role in reducing the cost and increasing the clinical utility of trials evaluating biomarker-guided treatment strategies.

Theranostic and molecular classification of breast cancer

CONTEXT

Despite advances in breast cancer management, women continue to relapse and die of breast cancer. Traditionally, evaluation for hormone receptors (estrogen and progesterone), as well as HER2 overexpression, have guided therapy-related decision-making because they are both prognostic and predictive indicators. However, there are limitations with those studies, which can lead to improper treatment. Gene signatures have recently been shown to be of value in identifying molecular portraits of breast carcinoma and are beginning to play role in management and treatment algorithms.

OBJECTIVE

To provide a summary of the prognostic and predictive indicators of breast cancer, such as hormone receptors, HER2, and molecular gene signatures that currently help guide clinical decision making.

DATA SOURCES

Published articles from peer-reviewed journals in PubMed (US National Library of Medicine).

CONCLUSIONS

Emerging evidence shows promise that, in addition to hormone receptors and HER2 studies, evaluating tumors with gene expression profiling can provide additional prognostic and predictive information, further aiding clinical management and leading to a more personalized approach to treating breast cancer.

Expression of estrogen-related gene markers in breast cancer tissue predicts aromatase inhibitor responsiveness

Aromatase inhibitors (AIs) are the most effective class of drugs in the endocrine treatment of breast cancer, with an approximate 50% treatment response rate. Our objective was to determine whether intratumoral expression levels of estrogen-related genes are predictive of AI responsiveness in postmenopausal women with breast cancer. Primary breast carcinomas were obtained from 112 women who received AI therapy after failing adjuvant tamoxifen therapy and developing recurrent breast cancer. Tumor ERα and PR protein expression were analyzed by immunohistochemistry (IHC). Messenger RNA (mRNA) levels of 5 estrogen-related genes–AKR1C3, aromatase, ERα, and 2 estradiol/ERα target genes, BRCA1 and PR–were measured by real-time PCR. Tumor protein and mRNA levels were compared with breast cancer progression rates to determine predictive accuracy. Responsiveness to AI therapy–defined as the combined complete response, partial response, and stable disease rates for at least 6 months–was 51%; rates were 56% in ERα-IHC-positive and 14% in ERα-IHC-negative tumors. Levels of ERα, PR, or BRCA1 mRNA were independently predictive for responsiveness to AI. In cross-validated analyses, a combined measurement of tumor ERα and PR mRNA levels yielded a more superior specificity (36%) and identical sensitivity (96%) to the current clinical practice (ERα/PR-IHC). In patients with ERα/PR-IHC-negative tumors, analysis of mRNA expression revealed either non-significant trends or statistically significant positive predictive values for AI responsiveness. In conclusion, expression levels of estrogen-related mRNAs are predictive for AI responsiveness in postmenopausal women with breast cancer, and mRNA expression analysis may improve patient selection.

Performance characteristics of the MammaPrint® breast cancer diagnostic gene signature

BACKGROUND

The analytical performance of multigene signatures depends on many parameters, including precision, repeatability, reproducibility and intratumor heterogeneity. Indicators such as sensitivity, specificity, positive predictive value and negative predictive value are typically used to define the clinical performance of a diagnostic test.

AIM

Here we study these performance characteristics of the MammaPrint^® (Agendia NV, Amsterdam, The Netherlands) 70-gene signature using the US FDA-recommended guidelines, as well as predetermined acceptance criteria.

RESULTS

The clinical and analytical performance characteristics show that MammaPrint is a robust, reproducible, precise test, with a maximum variation of 5% in multiple samplings of the same tissue.

CONCLUSION

MammaPrint is a reliable indicator of distant metastasis in early-stage breast cancer patients of all ages and is well suited for personalized medical care.

Systematic review on hormone receptor testing in breast cancer

Assessment of hormone receptors (estrogen and progesterone) helps to direct therapy for women with breast cancer. Immunohistochemistry is most commonly used to assess hormone receptor status and it is essential that these tests are performed accurately and reliably within and across laboratories. The overall purpose of this guideline is to improve the quality and accuracy of hormone receptor testing and its utility as a prognostic and predictive marker for invasive and in situ breast cancer. Medline, EMBASE, the Cochrane Database of Systematic Reviews, and abstracts from the San Antonio Breast Cancer Symposium were searched. An environmental scan of the internet and of international guideline developers and key organizations was performed. Preanalytic elements such as the collection, fixation, and storage of samples, and analytic elements such as selection of antibodies and scoring methods that seem to offer the best results for immunohistochemical assessment of hormone receptors are presented. Proficiency testing or quality assurance of immunohistochemistry is described.

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.

Barriers to the use of personalized medicine in breast cancer

PURPOSE

Personalized medicine--the use of genomics and molecular diagnostics to direct care decisions--may improve outcomes by more accurately individualizing treatment to patients. Using qualitative research, we explored care delivery barriers to the use of personalized medicine for patients with breast cancer using examples of BRCA and gene expression profile testing.

METHODS

We conducted 51 interviews with multidisciplinary stakeholders in breast cancer care: clinicians (n = 25) from three academic and nine nonacademic organizations, executives (n = 20) from four major private insurers, and patient advocates (n = 6).

RESULTS

Barriers were common to the BRCA and gene expression profile tests and were classified under two categories: poor coordination of tests relative to treatment decisions and reimbursement-related disincentives. Perception of specific barriers varied across groups. Difficulty coordinating diagnostics relative to decisions was the most frequent concern by clinicians (60%), but only 35% of payers and 17% of advocates noted this barrier. For 60% of payers, drug- and procedure-based reimbursement was a significant barrier, but only 40% of clinicians and none of the advocates expressed the same concern. The opinion that patient out-of-pocket expenses are a barrier varied significantly between advocates and clinicians (83% v 20%, P < .007), and advocates and payers (83% v 15%, P < .004). Barriers were reported to result in postponement or avoidance of tests, delayed treatment decisions, and proceeding with decisions before test results.

CONCLUSION

Poorly coordinated diagnostic testing and the current oncology reimbursement model are barriers to the use of genomic and molecular diagnostic tests in cancer care.

Cancer care Ontario guideline recommendations for hormone receptor testing in breast cancer

Hormone receptor testing (oestrogen and progesterone) in breast cancer at the time of primary diagnosis is used to guide treatment decisions. Accurate and standardised testing methods are critical to ensure the proper classification of the patient's hormone receptor status. Recommendations were developed to improve the quality and accuracy of hormone receptor testing based on a systematic review conducted jointly by the American Society of Clinical Oncology/College of American Pathologists and Cancer Care Ontario's Program in Evidence-Based Care. Evidence-based recommendations were formulated to set standards for optimising immunohistochemistry in assessing hormone receptor status, as well as assuring quality and proficiency between and within laboratories. A formal external review was conducted to validate the relevance of these recommendations. It is anticipated that widespread adoption of these guidelines will further improve the accuracy of hormone receptor testing in Canada.

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

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

Discovery of IL-18 as a novel secreted protein contributing to doxorubicin resistance by comparative secretome analysis of MCF-7 and MCF-7/Dox

Background

Resistance to chemotherapy is the major cause of failure in breast cancer treatment. Recent studies suggest that secreted proteins may play important roles in chemoresistance. We sought to systematically characterize secreted proteins associated with drug resistance, which may represent potential serum biomarkers or novel drug targets.

Methodology/Principal Findings

In the present work, we adopted the proteomic strategy of one-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to compare the secretome of MCF-7 and doxorubicin-resistant MCF-7/Dox. A total of 2,084 proteins were identified with at least two unique peptides in the conditioned media of two cell lines. By quantification with label-free spectral counting, 89 differentially expressed secreted proteins (DESPs) between the two cell lines were found. Among them, 57 DESPs were first found to be related to doxorubicin resistance in this work, including 24 extracellular matrix related proteins, 2 cytokines and 31 unclassified proteins. We focused on 13 novel DESPs with confirmed roles in tumor metastasis. Among them, the elevated expression of IL-18 in doxorubicin-resistant cell lines and breast tumor tissues was validated and its role in doxorubicin resistance was further confirmed by cell viability experiments in the presence or absence of this protein.

Conclusions/Significance

Comparative analysis of the secretome of MCF-7 and MCF-7/Dox identified novel secreted proteins related to chemotherapy resistance. IL-18 was further validated to contribute to doxorubicin resistance, in addition to its confirmed role in breast cancer metastasis. Due to its dual roles in both drug resistance and tumor metastasis, IL-18 may represent a useful drug target for breast cancer therapy.

Implication of tumor microenvironment in the resistance to chemotherapy in breast cancer patients

PURPOSE OF REVIEW

Chemotherapy is a cornerstone treatment in patients with early breast cancer. Although some cancer cell-related predictors are emerging, the indications of chemotherapy and the choice of chemotherapy regimen are not individualized enough, emphasizing the need for new predictors. This review will summarize recent advances concerning the implication of tumor microenvironment in the response to chemotherapy.

RECENT FINDINGS

In recent years, some data have emerged suggesting that microenvironment could be involved in chemotherapy efficacy. The infiltration of tumor by lymphocytes has been highly correlated with the sensitivity to chemotherapy. These data are consistent with the discovery that anthracyclines could induce immune activation through immunogenic cell death. At the opposite, gene expression analyses have suggested that a stroma signature could predict resistance to neoadjuvant chemotherapy. Finally, chemotherapy has been shown to induce a spike of progenitors for endothelial cells, a mechanism that in turns mediates angiogenesis repopulation.

SUMMARY

Preliminary data from pioneer studies suggest that tumor microenvironment could be involved in chemotherapy sensitivity and resistance. Such knowledge could generate two advances: simple predictors for chemotherapy efficacy based on pathology could be generated and strategies that aim at reversing drug resistance could be developed.

Gene expression profiling in breast cancer

BACKGROUND

Breast cancer is a heterogeneous group of different tumor subtypes that vary in prognosis and response to therapy. This heterogeneity has spawned an era of molecular assays striving to classify and thus predict outcome, thereby guiding the future in targeted personalized treatment strategies.

METHODS

This article provides an overview of the development and application of molecular assays as applied to breast cancer. Differences in the technology used for these tests as well as scientific evidence supporting the validity of the gene expression profile are discussed. Examples of the clinical applicability of these assays are provided, but these represent only a fraction of the potential uses yet to be discovered. A comparison of the three most commonly used assays is included.

RESULTS

Molecular assays have provided new genetic approaches to unravel the complexities of clinical specimens relevant to breast cancer treatment planning and assessment of outcome. In particular, on a molecular level specific to the woman's tumor, these assays allow a prediction of outcome (prognosis) in terms of low and high risk for the future development of distant metastatic disease. Additionally, one assay, Oncotype DX (Genomic Health Inc, Redwood City, CA), allows for the prediction of benefit of the addition of chemotherapy to hormone therapy alone.

CONCLUSIONS

While incorporation of molecular assays into the treatment planning strategy of breast cancer continues to be a work in progress, this approach is evolving quickly due to strong scientific evidence to become standard of practice in the near future. The possibilities of these assays in terms of clinical investigation are limitless, but currently their general applicability is limited to less than half of the population of women presenting with breast cancer.

A lower Allred score for progesterone receptor is strongly associated with a higher recurrence score of 21-gene assay in breast cancer

Among the 77 infiltrating breast carcinomas, we found that progesterone receptor (PR) expression was inversely associated with recurrence score (RS, p < .0001). RS is also significantly associated with tubule formation, mitosis, and luminal B subtype. The equation of RS = 17.489 + 2.071 (tubal formation) + 2.926 (mitosis) -2.408 (PR) -1.061 (HER2) + 7.051 (luminal A) + 29.172 (luminal B) predicts RS with an R² of 0.65. In conclusion, PR negativity, luminal B subtype, tubal formation, and mitosis are strongly correlated with a higher RS.

Prediction and prognosis: impact of gene expression profiling in personalized treatment of breast cancer patients

Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.

Human epidermal growth factor receptor 2 assessment in a case-control study: comparison of fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction performed by central laboratories

PURPOSE

The optimal method to assess human epidermal growth factor receptor 2 (HER2) status remains highly controversial. Before reporting patient HER2 results, American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines mandate that laboratories demonstrate ≥ 95% concordance to another approved laboratory or methodology. Here, we compare central laboratory HER2 assessed by fluorescence in situ hybridization (FISH) and quantitative reverse transcriptase polymerase chain reaction (RT-PCR) using Oncotype DX in lymph node-negative, chemotherapy-untreated patients from a large Kaiser Permanente case-control study.

PATIENTS AND METHODS

Breast cancer specimens from the Kaiser-Genomic Health study were examined. Central FISH assessment of HER2 amplification and polysomy 17 was conducted by PhenoPath Laboratories (ratios > 2.2, 1.8 to 2.2, and < 1.8 define HER2 positive, HER2 equivocal, and HER2 negative, respectively). HER2 expression by RT-PCR was conducted using Oncotype DX by Genomic Health (normalized expression units ≥ 11.5, 10.7 to < 11.5, and < 10.7 define HER2 positive, HER2 equivocal, and HER2 negative, respectively). Concordance analyses followed ASCO/CAP guidelines.

RESULTS

HER2 concordance by central FISH and central RT-PCR was 97% (95% CI, 96% to 99%). Twelve percent (67 of 568 patients) and 11% (60 of 568 patients) of patients were HER2 positive by RT-PCR and FISH, respectively. HER2-positive patients had increased odds of dying from breast cancer compared with HER2-negative patients. Polysomy 17 was demonstrated in 12.5% of all patients and 33% of FISH-positive patients. Nineteen of 20 FISH-positive patients with polysomy 17 were also RT-PCR HER2 positive. Although not statistically significantly different, HER2-positive/polysomy 17 patients tended to have the worst prognosis, followed by HER2-positive/eusomic, HER2-negative/polysomy 17, and HER2-negative/eusomic patients.

CONCLUSION

There is a high degree of concordance between central FISH and quantitative RT-PCR using Oncotype DX for HER2 status, and the assay warrants additional study in a trastuzumab-treated population.

Clinical implications of chemotherapy-induced tumor gene expression in human breast cancers

IMPORTANCE OF THE FIELD

There has been much interest in generating gene signatures to predict treatment response in breast cancer.

AREAS COVERED IN THIS REVIEW

There are at least 15 published studies that describe baseline tumor gene signatures predicting chemotherapy sensitivity. As an extension of these baseline studies, there have been at least 8 published studies evaluating chemotherapy-induced tumor genomic changes over time in human breast cancers.

WHAT THE READER WILL GAIN

Studies on chemotherapy-induced gene expression changes were reviewed in detail. Drug-induced biological changes within the tumor shed light on mechanisms of drug resistance and provided valuable insights regarding genes and pathways that were regulated by different drugs, including therapeutic targets that could be exploited to overcome resistance. One study also suggested post-chemotherapy gene signatures to be more predictive of response and survival than the unchallenged baseline signatures.

TAKE HOME MESSAGE

Studies on chemotherapy-induced changes, although informative, are logistically demanding to execute, often with significant attrition of collected samples resulting in small datasets. They are further limited by heterogeneity of study population, chemotherapy regimens used, timing of the post-therapy sample and definition of response endpoint, making cross-comparisons of studies and data interpretation difficult. Future studies should address these limitations, and should involve larger sample sets and prospective studies for validation.

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

In the last decade, the development of microarrays and the ability to perform massively parallel gene expression analysis of human tumours were received with great excitement by the scientific community. The promise of microarrays was of apocalyptic dimensions, with some experts envisaging that it would be a matter of a few years for this technology to replace traditional clinicopathological markers in clinical practice and treatment decision-making. The replacement of histopathology by high-tech and more objective approaches to cancer diagnosis, prognostication and prediction was, at that time, a foregone conclusion. Ten years after the initial publications of translational research studies using microarrays, one cannot deny that this technology has changed the way breast cancer is perceived. It has brought the concept of breast cancer heterogeneity to the forefront of cancer research, and the fact that distinct subtypes of breast cancer are completely different diseases that affect the same anatomical site. Furthermore, it has led to the development of prognostic and predictive 'gene signatures', which are yet to be fully incorporated into clinical practice. Importantly, though, the prognostic and predictive power of microarrays has been shown to be complementary to, rather than a replacement for, traditional clinicopathological parameters. Here we endeavour to provide a fair and balanced assessment of what microarray-based gene expression analysis has taught us in the last decade and its contribution to breast cancer classification, prognostication and prediction.

Genomic predictors of outcome and treatment response in breast cancer

Despite advances in breast cancer treatment and outcome over the last two decades, women continue to relapse and die of advanced disease. Historically, estrogen and progesterone receptor expression, HER2 overexpression and clinico-pathologic parameters have guided therapeutic decision making. However, there are limits to the risk estimation provided by these parameters, leading to potential overtreatment of low-risk disease and undertreatment of poor-risk disease. Genomic technologies now provide the opportunity to refine our therapeutic approach by individualizing treatment to patients' individual tumor profiles. Gene profiles or signatures are groupings of genes that are differentially expressed between tumors, reflecting differences in biologic behavior. Prognostic gene signatures stratify breast cancer patients by tumor natural history, regardless of the treatment employed. Currently, there are three commercially available prognostic gene signatures: Oncotype DX (Genomic Health, Inc.), MammaPrint (Agendia BV), and the HOXB13/IL17BR (H/I) ratio; (Theros H/ISM; bioTheranostics). Others under development include the Intrinsic Gene Set, the Rotterdam Signature, the Wound Response Indicator, and the Invasive Gene Signature. Predicative signatures classify patients based on responsiveness to specific therapies. Of the prognostic signatures, Oncotype DX has been shown to have predictive value for the incremental benefit of chemotherapy when added to a hormonal therapy regimen. Additional genetic profiles under development predict response to specific hormonal therapies, anthracyclines, and taxanes. Gene signatures have the potential to transform breast cancer treatment as it becomes tailored to each patient's tumor expression profile and significantly improve the outcomes of this disease.

Molecular markers of breast axillary lymph node metastasis

In breast cancer, axillary lymph node status is one of the most important prognostic variables and a crucial component to the staging system. Several clinico-histopathological parameters are considered to be strong predictors of metastasis; however, they fail to accurately classify breast tumors according to their clinical behavior and to predict which patients will have disease recurrence. Methods based on genome-wide microarray analyses have been used to identify molecular markers with respect to the development of axillary lymph node metastasis. Most of these markers can be detected in the primary tumors, which can potentially lead to the ability to identify patients at the time of diagnosis who are at high risk for lymph node metastasis, allowing for early intervention and more suitable adjuvant treatments.

T1N0 triple negative breast cancer: risk of recurrence and adjuvant chemotherapy

Adjuvant treatment of T1N0 breast cancer (BC) has evolved in recent years with chemotherapy options dependent on tumor size and cellular characteristics. Our goal is to describe the difference in outcome between T1N0 triple negative (TriNeg) and estrogen/progesterone receptor positive/her2/neu-negative BC. From our institute's registry, we identified primary BC patients diagnosed from 1998 to 2005, estrogen/progesterone receptor negative (ER-/PR-)/her-2/neu negative (her2-) (TriNeg = 110) and ER+/PR+/her2- (HR+/her2- = 919). Clinical diagnosis and treatment variables were chart abstracted. Vital and disease status were updated annually. Pearson chi-squared tests were used for bivariate analysis. Hazard ratios were calculated using the Cox proportional hazards model. Average patient age was 59 years, range 23-93 years and average length of follow-up was 4.22 years. T-stage distribution for HR+/her2- patients was 9% T1a (>0.1, < or = 0.5 cm), 34% T1b (>0.5 cm, < or = 1 cm), 57% T1c (>1 cm, < or = 2 cm) and for TriNeg, 6% T1a, 21% T1b, and 73% T1c. Sixty-five per cent of T1b and 73% T1c TriNeg patients received chemotherapy versus 7% of T1b and 32% of T1c HR+/her2- patients with TriNeg patients more likely to receive doxorubicin/cyclophosphamide/paclitaxel combined therapy. Recurrence rates were the following, T1b: 8.7%, TriNeg (2/23) versus 0%, HR+/her2- (0/315) and T1c: 8.8%, TriNeg (7/80) versus 2.1%, HR+/her2- (11/523). Five year relapse-free survival was 98% in the HR+/her2- group and 89% in the TriNeg group (log rank test = 27.77, p < 0.001). The hazard ratio for recurrence in the TriNeg group was 6.57 (95% CI = 2.34, 18.49) adjusted for age, tumor size, and adjuvant chemotherapy. Triple negative T1N0 patients have greater recurrence risk in spite of more aggressive therapy by both number treated and adjuvant chemotherapy type even in a low-risk category. New treatment modalities specific for triple negative disease are urgently needed.

Recommendations from the EGAPP Working Group: can tumor gene expression profiling improve outcomes in patients with breast cancer?

SUMMARY OF RECOMMENDATIONS

The EGAPP Working Group (EWG) found insufficient evidence to make a recommendation for or against the use of tumor gene expression profiles to improve outcomes in defined populations of women with breast cancer. For one test, the EWG found preliminary evidence of potential benefit of testing results to some women who face decisions about treatment options (reduced adverse events due to low risk women avoiding chemotherapy), but could not rule out the potential for harm for others (breast cancer recurrence that might have been prevented). The evidence is insufficient to assess the balance of benefits and harms of the proposed uses of the tests. The EWG encourages further development and evaluation of these technologies.

RATIONALE

The measurement of gene expression in breast tumor tissue is proposed as a way to estimate the risk of distant disease recurrence in order to provide additional information beyond current clinicopathological risk stratification and to influence decisions about treatment in order to improve health outcomes. Based on their review of the EGAPP-commissioned evidence report, Impact of Gene Expression Profiling Tests on Breast Cancer Outcomes and other data summaries, the EWG found no direct evidence linking tumor gene expression profiling of women with breast cancer to improved outcomes, and inadequate evidence to construct an evidence chain. However, further evaluation on the clinical utility of some tests and management algorithms, including well-designed randomized controlled trials, is warranted.

ANALYTIC VALIDITY

Some data on technical performance of assays were identified for MammaPrint and Oncotype DX, though estimates of analytic sensitivity and specificity could not be made. Published performance data on the laboratory developed Quest H:I Test were limited. Overall, the EWG found the evidence to be inadequate.

CLINICAL VALIDITY

The EWG found adequate evidence regarding the association of the Oncotype DX Recurrence Score with disease recurrence and adequate evidence for response to chemotherapy. The EWG found adequate evidence to characterize the association of MammaPrint with future metastases, but inadequate evidence to assess the added value to standard risk stratification, and could not determine the population to which the test would best apply. The evidence was inadequate to characterize the clinical validity of the Quest H:I Test.

CLINICAL UTILITY

The EWG found no evidence regarding the clinical utility of the MammaPrint and Quest H:I Ratio tests, and inadequate evidence regarding Oncotype DX. These technologies have potential for both benefit and harm.

CONTEXTUAL ISSUES

The EWG reviewed economic studies that used modeling to predict potential effects of using gene profiling, and judged the evidence inadequate.