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

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Recommendations from the European Commission Initiative on Breast Cancer for multigene testing to guide the use of adjuvant chemotherapy in patients with early breast cancer, hormone receptor positive, HER-2 negative

Background

Predicting the risk of recurrence and response to chemotherapy in women with early breast cancer is crucial to optimise adjuvant treatment. Despite the common practice of using multigene tests to predict recurrence, existing recommendations are inconsistent. Our aim was to formulate healthcare recommendations for the question “Should multigene tests be used in women who have early invasive breast cancer, hormone receptor-positive, HER2-negative, to guide the use of adjuvant chemotherapy?”

Methods

The European Commission Initiative on Breast Cancer (ECIBC) Guidelines Development Group (GDG), a multidisciplinary guideline panel including experts and three patients, developed recommendations informed by systematic reviews of the evidence. Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision frameworks were used. Four multigene tests were evaluated: the 21-gene recurrence score (21-RS), the 70-gene signature (70-GS), the PAM50 risk of recurrence score (PAM50-RORS), and the 12-gene molecular score (12-MS).

Results

Five studies (2 marker-based design RCTs, two treatment interaction design RCTs and 1 pooled individual data analysis from observational studies) were included; no eligible studies on PAM50-RORS or 12-MS were identified and the GDG did not formulate recommendations for these tests.

Conclusions

The ECIBC GDG suggests the use of the 21-RS for lymph node-negative women (conditional recommendation, very low certainty of evidence), recognising that benefits are probably larger in women at high risk of recurrence based on clinical characteristics. The ECIBC GDG suggests the use of the 70-GS for women at high clinical risk (conditional recommendation, low certainty of evidence), and recommends not using 70-GS in women at low clinical risk (strong recommendation, low certainty of evidence).

The IHC4+C score: an affordable and reproducible non-molecular decision-aid in hormone receptor-positive breast cancer. Does it still hold value for patients in 2020?

AIM

The majority of women diagnosed with early breast cancer have hormone-receptor positive (HR+)/HER2-negative disease. Adjuvant endocrine therapy provides substantial risk reduction benefits in virtually all patients. The role of adjuvant chemotherapy in certain subsets of patients is equivocal. This paper sought to evaluate the role of the IHC4+C score to aid this clinical decision in addition to providing an overview of the current molecular and non- molecular tools available in the adjuvant setting.

METHODS

This prospective study included 53 post-operative HR+/HER2- negative early breast cancer patients selected from the multidiscipliniary team meeting between August 2017 and January 2020. IHC4+C testing was requested by clinicians for patients in whom the availability of the score may have impacted adjuvant decision-making. Adjuvant treatment decisions were recorded at three time points (prior and post IHC4+C scoring as well as the patient's final decision). The primary goal was the proportion of patients who were spared chemotherapy following the availability of IHC4+C scores to impact on clinicians' recommendations for adjuvant systemic therapy.

RESULTS

A total of 34 patients (64%) were initially recommended to undergo chemotherapy or to consider chemotherapy. With the availability of the IHC4+C score, only 17 patients (32%) underwent chemotherapy, demonstrating a substantial reduction in the frequency of chemotherapy prescribing.

CONCLUSION

This study demonstrates that when utilized appropriately in a multidisciplinary setting, the IHC4+C algorithm is an alternative, reproducible and affordable tool with a proven capacity to stratify risk and to spare a large proportion of patients from undergoing chemotherapy.

The Potential Use of Tumour-Based Prognostic and Predictive Tools in Older Women with Primary Breast Cancer: A Narrative Review

A move is under way towards personalised cancer treatment, where tumour biology of an individual patient is examined to give unique predictive and prognostic information. This is extremely important in the setting of older women, who have treatment-specific goals which may differ from their younger counterparts, and may include conservation of quality of life rather than curative intent of treatment. One method employed to assist with this is the use of tumour-based prognostic and predictive tools. This article explores six of the most common tumour-based tools currently available on the market: MammaPrint, Oncotype DX, Mammostrat, Prosigna, EndoPredict, IHC4. The article discusses the creation and validation of these tools, their use and validation in older women, and future directions in the field. With the exception of Oncotype Dx, which has also been licensed for prediction of response from adjuvant chemotherapy, these tools have been licensed for use as prognostic tools only, mainly in the setting of adjuvant therapy following surgery. The evidence base for use in older women is strongest for Mammostrat and PAM50, although overall the evidence is much weaker than that in younger women. Where older women have been included in validation studies, this is often in small numbers, or the exact proportion of older women is unknown. In practice, all six of the tools are recommended to be utilised on surgical excision specimens, as well as in core needle biopsy (CNB) specimens in all of the tools except Mammostrat. This is extremely important in the setting of older women, of whom a large proportion do not undergo surgery. The suggested nature of the sample is formalin-fixed paraffin-embedded in all the tools except MammaPrint, which can also be performed on fresh-frozen samples. Future development of prognostic tools in older women with breast cancer should focus on treatment dilemmas specific to this population. This includes the decision of primary treatment between surgery or endocrine therapy and decisions regarding adjuvant therapy, in particular, chemotherapy.

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.

Combined quantitative measures of ER, PR, HER2, and KI67 provide more prognostic information than categorical combinations in luminal breast cancer

Although most women with luminal breast cancer do well on endocrine therapy alone, some will develop fatal recurrence thereby necessitating the need to prospectively determine those for whom additional cytotoxic therapy will be beneficial. Categorical combinations of immunohistochemical measures of ER, PR, HER2, and KI67 are traditionally used to classify patients into luminal A-like and B-like subtypes for chemotherapeutic reasons, but this may lead to the loss of prognostically relevant information. Here, we compared the prognostic value of quantitative measures of these markers, combined in the IHC4-score, to categorical combinations in subtypes. Using image analysis-based scores for all four markers, we computed the IHC4-score for 2498 patients with luminal breast cancer from two European study populations. We defined subtypes (A-like (ER + and PR + : and HER2- and low KI67) and B-like (ER + and/or PR + : and HER2 + or high KI67)) by combining binary categories of these markers. Hazard ratios and 95% confidence intervals for associations with 10-year breast cancer-specific survival were estimated in Cox proportional-hazard models. We accounted for clinical prognostic factors, including grade, tumor size, lymph-nodal involvement, and age, by using the PREDICT-score. Overall, Subtypes [hazard ratio (95% confidence interval) B-like vs. A-like = 1.64 (1.25-2.14); P-value < 0.001] and IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.32 (1.20-1.44); P-value < 0.001] were prognostic in univariable models. However, IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.24 (1.11-1.37); P-value < 0.001; likelihood ratio chi-square (LRχ2) = 12.5] provided more prognostic information than Subtype [hazard ratio (95% confidence interval) B-like vs. A-like = 1.38 (1.02-1.88); P-value = 0.04; LRχ2 = 4.3] in multivariable models. Further, higher values of the IHC4-score were associated with worse prognosis, regardless of subtype (P-heterogeneity = 0.97). These findings enhance the value of the IHC4-score as an adjunct to clinical prognostication tools for aiding chemotherapy decision-making in luminal breast cancer patients, irrespective of subtype.

Risk stratification of ER-positive breast cancer patients: A multi-institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26

The skyrocketing cost of health-care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX^® (ODX) testing. This study is a multi-institutional validation of that algorithmic model in 620 additional estrogen receptor positive breast cancer cases, with outcome data on 310 cases, named in this study as the Rochester Modified Magee algorithm (RoMMa). RoMMa correctly predicted 85% (140/164) and 100% (17/17) of cases to have a low- or high-risk ODX recurrence score, respectively, consistent with the original publication. Applying our own risk stratification criteria, in patients who received appropriate hormonal therapy, only one of the 45 (2.0%) patients classified as low risk by our original algorithm have been associated with a breast cancer recurrence over 5-10 years of follow-up. Eight of 116 (7.0%) patients classified as low risk by ODX have been associated with a breast cancer recurrence with up to 11 years of follow-up. In addition, 524 of 537 (98%) cases from our total population (n = 903) with an average modified Magee score ≤18 had an ODX recurrence score <26. Patients with an average modified Magee score ≤18 or >30 may not need to be sent out for ODX testing. By avoiding these cases sending out for ODX testing, the potential cost savings to the health-care system in 2018 are estimated to have been over $100,000,000.

Core needle biopsy as an alternative to whole section in IHC4 score assessment for breast cancer prognostication

AIMS

IHC4 score, based on expression of four routine markers (oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and proliferation marker, Ki67), is a recently developed, cost-effective prognostic tool in breast cancer. Possibly, the score may be useful also in advanced diseases where only core needle biopsy (CNB) is available and neoadjuvant therapy. However, its studies on CNB are scant. This study examined whether IHC4 score assessment on CNB is comparable to that from whole section (WS).

METHODS

Immunohistochemical (IHC) analysis was performed for ER, PR, HER2 and Ki67 on 108 paired CNB and WS to evaluate IHC4 score (with follow-up range 1-230 months and 5 relapse/death). Concordance between the two was examined. Factors that affected the concordance were analysed. Additionally, IHC4 score was compared with Nottingham Prognostic Index (NPI).

RESULTS

There was moderate concordance between IHC4 score on CNB and WS (all cases: κ=0.699, p<0.001; ER+ cases: κ=0.595, p<0.001). Among the IHC4 components, concordance for HER2 was the poorest (κ=0.178, p<0.001 in all cases; ER+ cases: κ=0.082, p<0.097). Significant factors affecting concordance between CNB and WS included number of cores, total core length and percentage of tumour cells in cores (p≤0.030), indicating the importance of sufficient sampling. Interestingly, the concordance was also affected by patients' age (p=0.039). There was poor agreement between IHC4 score and NPI (κ≤0.160).

CONCLUSION

Our results suggested that IHC4 score can be used on adequately sampled CNB. Its poor agreement with NPI highlights the independence of the two factors.

Etiology of hormone receptor positive breast cancer differs by levels of histologic grade and proliferation

Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ breast cancer cases and 26,281 controls from 11 epidemiological studies. Proliferation was determined by centralized automated measures of KI67 in tissue microarrays. Odds ratios (OR), 95% confidence intervals (CI) and p-values for case-case and case-control comparisons for risk factors in relation to levels of grade and quartiles (Q1-Q4) of KI67 were estimated using polytomous logistic regression models. Case-case comparisons showed associations between nulliparity and high KI67 [OR (95% CI) for Q4 vs. Q1 = 1.54 (1.22, 1.95)]; obesity and high grade [grade 3 vs. 1 = 1.68 (1.31, 2.16)] and current use of combined hormone therapy (HT) and low grade [grade 3 vs. 1 = 0.27 (0.16, 0.44)] tumors. In case-control comparisons, nulliparity was associated with elevated risk of tumors with high but not low levels of proliferation [1.43 (1.14, 1.81) for KI67 Q4 vs. 0.83 (0.60, 1.14) for KI67 Q1]; obesity among women ≥50 years with high but not low grade tumors [1.55 (1.17, 2.06) for grade 3 vs. 0.88 (0.66, 1.16) for grade 1] and HT with low but not high grade tumors [3.07 (2.22, 4.23) for grade 1 vs. 0.85 (0.55, 1.30) for grade 3]. Menarcheal age and family history were similarly associated with HR+ tumors of different grade or KI67 levels. These findings provide insights into the etiologic heterogeneity of HR+ tumors.

A combination of Nottingham prognostic index and IHC4 score predicts pathological complete response of neoadjuvant chemotherapy in estrogen receptor positive breast cancer

Pathologic complete response (pCR) prediction after neoadjuvant chemotherapy (NAC) is important for clinical decision-making in breast cancer. This study investigated the predictive value of Nottingham prognostic index (NPI), Immunohistochemical four (IHC4) score and a new predictive index combined with them in estrogen-positive (ER+) breast cancer following NAC. We retrospectively gathered clinical data of 739 ER+ breast cancer patients who received NAC from two cancer centers. We developed a new predictive biomarker named NPI+IHC4 to predict pCR in ER+ breast cancer in a training set (n=443) and validated it in an external validation set (n=296). The results showed that a lower IHC4 score, NPI and NPI+IHC4 were significantly associated a high pCR rate in the entire cohort. In the study set, NPI+IHC4 showed a better sensitivity and specificity for pCR prediction (AUC 0.699, 95% CI 0.626-0.772) than IHC4 score (AUC 0.613, 95% CI 0.533-0.692), NPI (AUC 0.576, 95% CI 0.494-0.659), tumor size (AUC 0.556, 95% CI 0.481-0.631) and TNM stage (AUC 0.521, 95% CI 0.442-0.601). In the validation set, NPI+IHC4 had a better predictive value for pCR (AUC 0.665, 95% CI 0.579-0.751) than IHC4 score or NPI alone. In addition, ER+ patients with lower IHC4, NPI and NPI+IHC4 scores had significantly better DFS in both study and validation sets. In summary, NPI+IHC4 can predict pCR following NAC and prognosis in ER+ breast cancer, which is cost-effect and potentially more useful in guiding decision-making regarding NAC in clinical practice. Further validation is needed in prospective clinical trials with larger cohorts of patients.

Novel Predictors of Breast Cancer Survival Derived from miRNA Activity Analysis

Purpose: Breast cancer is among the leading causes of cancer-related death; discovery of novel prognostic markers is needed to improve outcomes. Combining systems biology and epidemiology, we investigated miRNA-associated genes and breast cancer survival in a well-characterized population-based study.Experimental Design: A recently developed algorithm, ActMiR, was used to identify key miRNA "activities" corresponding to target gene degradation, which were predictive of breast cancer mortality in published databases. We profiled miRNA-associated genes in tumors from our well-characterized population-based cohort of 606 women with first primary breast cancer. Cox proportional hazards models were used to estimate HRs and 95% confidence intervals (CI), after 15+ years of follow-up with 119 breast cancer-specific deaths.Results: miR-500a activity was identified as a key miRNA for estrogen receptor-positive breast cancer mortality using public databases. From a panel of 161 miR-500a-associated genes profiled, 73 were significantly associated with breast cancer-specific mortality (FDR < 0.05) in our population, among which two clusters were observed to have opposing directions of association. For example, high level of SUSD3 was associated with reduced breast cancer-specific mortality (HR = 0.3; 95% CI, 0.2-0.4), whereas the opposite was observed for TPX2 (HR = 2.7; 95% CI, 1.8-3.9). Most importantly, we identified set of genes for which associations with breast cancer-specific mortality were independent of known prognostic factors, including hormone receptor status and PAM50-derived risk-of-recurrence scores. These results are validated in independent datasets.Conclusions: We identified novel markers that may improve prognostic efficiency while shedding light on molecular mechanisms of breast cancer progression. Clin Cancer Res; 24(3); 581-91. ©2017 AACR.

Evaluation of applying IHC4 as a prognostic model in the translational study of Intergroup Exemestane Study (IES): PathIES

BACKGROUND

Intergroup Exemestane Study (IES) was a randomised study that showed a survival benefit of switching adjuvant endocrine therapy after 2-3 years from tamoxifen to exemestane. This PathIES aimed to assess the role of immunohistochemical (IHC)4 score in determining the relative sensitivity to either tamoxifen or sequential treatment with tamoxifen and exemestane.

PATIENTS AND METHODS

Primary tumour samples were available for 1274 patients (27% of IES population). Only patients for whom the IHC4 score could be calculated (based on oestrogen receptor, progesterone receptor, HER2 and Ki67) were included in this analysis (N = 430 patients). The clinical score (C) was based on age, grade, tumour size and nodal status. The association of clinicopathological parameters, IHC4(+C) scores and treatment effect with time to distant recurrence-free survival (TTDR) was assessed in univariable and multivariable Cox regression analyses. A modified clinical score (PathIEscore) (N = 350) was also estimated.

RESULTS

Our results confirm the prognostic importance of the original IHC4, alone and in conjunction with clinical scores, but no significant difference with treatment effects was observed. The combined IHC4 + Clinical PathIES score was prognostic for TTDR (P < 0.001) with a hazard ratio (HR) of 5.54 (95% CI 1.29-23.70) for a change from 1st quartile (Q1) to Q1-Q3 and HR of 15.54 (95% CI 3.70-65.24) for a change from Q1 to Q4.

CONCLUSION

In the PathIES population, the IHC4 score is useful in predicting long-term relapse in patients who remain disease-free after 2-3 years. This is a first trial to suggest the extending use of IHC4+C score for prognostic indication for patients who have switched endocrine therapies at 2-3 years and who remain disease-free after 2-3 years.

Breast cancer subtype discrimination using standardized 4-IHC and digital image analysis

Breast cancer is a heterogeneous disease. Surrogate classification of intrinsic subtypes of invasive carcinomas by combined immunohistochemistry for estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 (4-IHC) has increased steadily since the 2011 St Gallen symposium, due to its rapid subtyping of tumors at a reasonable cost. An important step in improving 4-IHC reproducibility and reliability will be to provide reference values from the routine use of standardized 4-IHC followed by image analysis. The aims of the current study were (1) to analyze invasive breast carcinomas using standardized 4-IHC and quantitative image analysis and (2) to compare the results obtained in the classification of biological subtypes using current Ki67 and PR threshold values proposed by different authors to sub-classifying the luminal A-like and the luminal B-like (HER2-negative) subtypes. Five hundred twenty-one tumors were analyzed by standardized immunohistochemistry, with automatic image analysis, and HER2 FISH technique. Positivity for ER was found in 82.7% and for PR in 70.1% of cases. Using the Allred scoring system, hormone receptor results showed a bimodal distribution, particularly for ER. HER2 positivity was found in 15.7% of cases, and the mean Ki67 score was 32.3%. Using the most recently proposed surrogate definitions for the classification of luminal breast cancer subtypes, the percentages of different subtypes that we found were similar to those published with genomic platforms: 40.7% luminal A-like, 32.4% luminal B-like/HER2-negative, 9.8% luminal B-like/HER2-positive, 6.0% HER2-positive, and 11.1% triple negative. Standardized 4-IHC with automatic image analysis constitutes a low-cost method for surrogate definitions of biological subtypes of breast cancer that delivers accurate results in a day.

Relationship between IHC4 score and response to neo-adjuvant chemotherapy in estrogen receptor-positive breast cancer

AIMS

To determine whether IHC4 score assessed on pre-treatment core biopsies (i) predicts response to neo-adjuvant chemotherapy in ER-positive (ER+) breast cancer; (ii) provides more predictive information than Ki67 alone.

METHODS

113 patients with ER+ primary breast cancer treated with neo-adjuvant chemotherapy at the Royal Marsden Hospital between 2002 and 2010 were included in the study. Pathologic assessment of the excision specimen was made for residual disease. IHC4 was determined on pre-treatment core biopsies, blinded to clinical outcome, by immunohistochemistry using quantitative scoring of ER (H-score), PgR (%) and Ki67 (%). Determination of HER2 status was made by immunohistochemistry and fluorescent in situ hybridization for 2+ cases. IHC4 and Ki67 scores were tested for their association with pathological complete response (pCR) rate and residual cancer burden (RCB) score.

RESULTS

18 (16%) of the 113 patients and 8 (9%) of the 88 HER2-ve cases achieved pCR. Ki67 and IHC4 score were both positively associated with achievement of pCR (P < 10-7 and P < 10-9, respectively) and RCB0+1 (P < 10-5 and P < 10-9, respectively) following neo-adjuvant chemotherapy in all patients. Rates of pCR+RCB1 were 45 and 66% in the highest quartiles of Ki67 and IHC4 scores, respectively. In ER+HER2-ve cases, pCR+RCB1 rates were 35% and in the highest quartile of both Ki67 and IHC4. There were no pCRs in the lower half of IHC4 or Ki67 scores.

CONCLUSIONS

IHC4 was strongly predictive of pCR or near pCR in ER+ breast cancers following neo-adjuvant chemotherapy. Ki67 was an important component of this predictive ability, but was not as predictive as IHC4.

Adjuvant treatment recommendations for patients with ER-positive/HER2-negative early breast cancer by Swiss tumor boards using the 21-gene recurrence score (SAKK 26/10)

Background

To evaluate the effect of Recurrence Score® results (RS; Oncotype DX® multigene assay ODX) on treatment recommendations by Swiss multidisciplinary tumor boards (TB).

Methods

SAKK 26/10 is a multicenter, prospective cohort study of early breast cancer patients: Eligibility: R0-resection, ≥10% ER+ malignant cells, HER2–, pN0/pN1a. Patients were stratified into low-risk (LR) and non-low-risk (NLR) groups based on involved nodes (0 vs 1–3) and five additional predefined risk factors. Recommendations were classified as hormonal therapy (HT) or chemotherapy plus HT (CT + HT). Investigators were blinded to the statistical analysis plan. A 5%/10% rate of recommendation change in LR/NLR groups, respectively, was assumed independently of RS (null hypotheses).

Results

Two hundred twenty two evaluable patients from 18 centers had TB recommendations before and after consideration of the RS result. A recommendation change occurred in 45 patients (23/154 (15%, 95% CI 10–22%) in the LR group and 22/68 (32%, 95% CI 22–45%) in the NLR group). In both groups the null hypothesis could be rejected (both p < 0.001). Specifically, in the LR group, only 5/113 (4%, 95% CI 1–10%) with HT had a recommendation change to CT + HT after consideration of the RS, while 18/41 (44%, 95% CI 28–60%) of patients initially recommended CT + HT were subsequently recommended only HT. In the NLR group, 3/19 (16%, 95% CI 3–40%) patients were changed from HT to CT + HT, while 19/48 (40%, 95% CI 26–55%) were changed from CT + HT to HT.

Conclusion

There was a significant impact of using the RS in the LR and the NLR group but only 4% of LR patients initially considered for HT had a recommendation change (RC); therefore these patients could forgo ODX testing. A RC was more likely for NLR patients considered for HT. Patients considered for HT + CT have the highest likelihood of a RC based on RS.

Pathologic diagnosis of breast cancer patients: evolution of the traditional clinical-pathologic paradigm toward "precision" cancer therapy

We present an updated account of breast cancer treatment and of progress toward "precision" cancer therapy; we focus on new developments in diagnostic molecular pathology and breast cancer that have emerged during the past 2 years. Increasing awareness of new prognostic and predictive methodologies, and introduction of next generation sequencing has increased understanding of both tumor biology and clinical behavior, which offers the possibility of more appropriate therapeutic choices. It remains unclear which of these testing methodologies provides the most informative and cost-effective actionable results for predictive and prognostic pathology. It is likely, however, that an integrated "step-wise" approach that uses the traditional clinical-pathologic paradigms coordinated with molecular characterization of breast tumor tissue, will offer the most comprehensive and cost-effective options for individualized, "precision" therapy for patients with breast cancer.

Molecular stratification of early breast cancer identifies drug targets to drive stratified medicine

Many women with hormone receptor-positive early breast cancer can be managed effectively with endocrine therapies alone. However, additional systemic chemotherapy treatment is necessary for others. The clinical challenges in managing high-risk women are to identify existing and novel druggable targets, and to identify those who would benefit from these therapies. Therefore, we performed mRNA abundance analysis using the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial pathology cohort to identify a signature of residual risk following endocrine therapy and pathways that are potentially druggable. A panel of genes compiled from academic and commercial multiparametric tests as well as genes of importance to breast cancer pathogenesis was used to profile 3825 patients. A signature of 95 genes, including nodal status, was validated to stratify endocrine-treated patients into high-risk and low-risk groups based on distant relapse-free survival (DRFS; Hazard Ratio = 5.05, 95% CI 3.53-7.22, p = 7.51 × 10-19). This risk signature was also found to perform better than current multiparametric tests. When the 95-gene prognostic signature was applied to all patients in the validation cohort, including patients who received adjuvant chemotherapy, the signature remained prognostic (HR = 4.76, 95% CI 3.61-6.28, p = 2.53× 10-28). Functional gene interaction analyses identified six significant modules representing pathways involved in cell cycle control, mitosis and receptor tyrosine signaling; containing a number of genes with existing targeted therapies for use in breast or other malignancies. Thus the identification of high-risk patients using this prognostic signature has the potential to also prioritize patients for treatment with these targeted therapies.

A novel quantitative immunohistochemistry method for precise protein measurements directly in formalin-fixed, paraffin-embedded specimens: analytical performance measuring HER2

In clinical routine pathology today, detection of protein in intact formalin-fixed, paraffin-embedded tissue is limited to immunohistochemistry, which is semi-quantitative. This study presents a new and reliable quantitative immunohistochemistry method, qIHC, based on a novel amplification system that enables quantification of protein directly in formalin-fixed, paraffin-embedded tissue by counting of dots. The qIHC technology can be combined with standard immunohistochemistry, and assessed using standard bright-field microscopy or image analysis. The objective was to study analytical performance of the qIHC method. qIHC was tested under requirements for an analytical quantitative test, and compared with ELISA and flow cytometry for quantitative protein measurements. Human epidermal growth factor receptor 2 (HER2) protein expression was measured in five different cell lines with HER2 expression from undetectable with immunohistochemistry to strong positive staining (IHC 3+). Repeatability, reproducibility, robustness, linearity, dynamic range, sensitivity, and quantification limits were evaluated. Reproducibility and robustness were assessed in a setup to resemble daily work in a laboratory using a commercial immunohistochemistry platform. In addition, qIHC was correlated to standard HER2 immunohistochemistry in 44 breast cancer specimens. For all evaluated parameters, qIHC performance was either comparable or better than the reference methods. Furthermore, qIHC has a lower limit of detection than both immunohistochemistry and the ELISA reference method, and demonstrated ability to measure HER2 accurately and precise within a large dynamic range. In conclusion, the results show that qIHC provides a sensitive, quantitative, accurate, and robust assay for measurement of protein expression in formalin-fixed, paraffin-embedded cell lines, and tissue.

OPTIMA prelim: a randomised feasibility study of personalised care in the treatment of women with early breast cancer

BACKGROUND

There is uncertainty about the chemotherapy sensitivity of some oestrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancers. Multiparameter assays that measure the expression of several tumour genes simultaneously have been developed to guide the use of adjuvant chemotherapy for this breast cancer subtype. The assays provide prognostic information and have been claimed to predict chemotherapy sensitivity. There is a dearth of prospective validation studies. The Optimal Personalised Treatment of early breast cancer usIng Multiparameter Analysis preliminary study (OPTIMA prelim) is the feasibility phase of a randomised controlled trial (RCT) designed to validate the use of multiparameter assay directed chemotherapy decisions in the NHS.

OBJECTIVES

OPTIMA prelim was designed to establish the acceptability to patients and clinicians of randomisation to test-driven treatment assignment compared with usual care and to select an assay for study in the main RCT.

DESIGN

Partially blinded RCT with adaptive design.

SETTING

Thirty-five UK hospitals.

PARTICIPANTS

Patients aged ≥ 40 years with surgically treated ER-positive HER2-negative primary breast cancer and with 1-9 involved axillary nodes, or, if node negative, a tumour at least 30 mm in diameter.

INTERVENTIONS

Randomisation between two treatment options. Option 1 was standard care consisting of chemotherapy followed by endocrine therapy. In option 2, an Oncotype DX(®) test (Genomic Health Inc., Redwood City, CA, USA) performed on the resected tumour was used to assign patients either to standard care [if 'recurrence score' (RS) was > 25] or to endocrine therapy alone (if RS was ≤ 25). Patients allocated chemotherapy were blind to their randomisation.

MAIN OUTCOME MEASURES

The pre-specified success criteria were recruitment of 300 patients in no longer than 2 years and, for the final 150 patients, (1) an acceptance rate of at least 40%; (2) recruitment taking no longer than 6 months; and (3) chemotherapy starting within 6 weeks of consent in at least 85% of patients.

RESULTS

Between September 2012 and 3 June 2014, 350 patients consented to join OPTIMA prelim and 313 were randomised; the final 150 patients were recruited in 6 months, of whom 92% assigned chemotherapy started treatment within 6 weeks. The acceptance rate for the 750 patients invited to participate was 47%. Twelve out of the 325 patients with data (3.7%, 95% confidence interval 1.7% to 5.8%) were deemed ineligible on central review of receptor status. Interviews with researchers and recordings of potential participant consultations made as part of the integral qualitative recruitment study provided insights into recruitment barriers and led to interventions designed to improve recruitment. Patient information was changed as the result of feedback from three patient focus groups. Additional multiparameter analysis was performed on 302 tumour samples. Although Oncotype DX, MammaPrint(®)/BluePrint(®) (Agendia Inc., Irvine, CA, USA), Prosigna(®) (NanoString Technologies Inc., Seattle, WA, USA), IHC4, IHC4 automated quantitative immunofluorescence (AQUA(®)) [NexCourse BreastTM (Genoptix Inc. Carlsbad, CA, USA)] and MammaTyper(®) (BioNTech Diagnostics GmbH, Mainz, Germany) categorised comparable numbers of tumours into low- or high-risk groups and/or equivalent molecular subtypes, there was only moderate agreement between tests at an individual tumour level (kappa ranges 0.33-0.60 and 0.39-0.55 for tests providing risks and subtypes, respectively). Health economics modelling showed the value of information to the NHS from further research into multiparameter testing is high irrespective of the test evaluated. Prosigna is currently the highest priority for further study.

CONCLUSIONS

OPTIMA prelim has achieved its aims of demonstrating that a large UK clinical trial of multiparameter assay-based selection of chemotherapy in hormone-sensitive early breast cancer is feasible. The economic analysis shows that a trial would be economically worthwhile for the NHS. Based on the outcome of the OPTIMA prelim, a large-scale RCT to evaluate the clinical effectiveness and cost-effectiveness of multiparameter assay-directed chemotherapy decisions in hormone-sensitive HER2-negative early breast would be appropriate to take place in the NHS.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN42400492.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 10. See the NIHR Journals Library website for further project information. The Government of Ontario funded research at the Ontario Institute for Cancer Research. Robert C Stein received additional support from the NIHR University College London Hospitals Biomedical Research Centre.

Ki67/SATB1 ratio is an independent prognostic factor of overall survival in patients with early hormone receptor-positive invasive ductal breast carcinoma

Biological diversity of breast cancer presents challenges for personalized therapy and necessitates multiparametric approaches to understand and manage the disease. Multiple protein biomarkers tested by immunohistochemistry (IHC), followed by digital image analysis and multivariate statistics of the data, have been shown to be effective in exploring latent profiles of tumor tissue immunophenotype. In this study, based on tissue microarrays of 107 patients with hormone receptor (HR) positive invasive ductal breast carcinoma, we investigated the prognostic value of the integrated immunophenotype to predict overall survival (OS) of the patients. A set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16) was used. The main factor of the variance was characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α; it was associated with histological grade but did not predict OS. The second factor was driven by SATB1 expression along with moderate positive HIF-1α and weak negative Ki67 loadings. Importantly, this factor did not correlate with any clinicopathologic parameters, but was an independent predictor of better OS. Ki67 and SATB1 did not reach statistical significance as single predictors; however, high Ki67/SATB1 ratio was an independent predictor of worse OS. In addition, our data indicate potential double prognostic meaning of HIF-1α expression in breast cancer and necessitate focused studies, taking into account the immunophenotype interactions and tissue heterogeneity aspects.

Comprehensive Immunohistochemistry: Digital, Analytical and Integrated

Immunohistochemistry (IHC) is widely used in contemporary pathology as a diagnostic and, increasingly, as a prognostic and predictive tool. The main value of the method today comes from a sensitive and specific detection of a protein of interest in the context of tissue architecture and cell populations. One of the major limitations of conventional IHC is related to the fact that the results are usually obtained by visual qualitative or semiquantitative evaluation. While this is sufficient for diagnostic purposes, measurement of prognostic and predictive biomarkers requires better accuracy and reproducibility. Also, objective evaluation of the spatial heterogeneity of biomarker expression as well as the development of combined/integrated biomarkers are in great demand. On the other end of the scale, the rapid development of tissue proteomics accounting for 2D spatial aspects has led to a disruptive concept of next-generation IHC, promising high multiplexing and broad dynamic range quantitative/spatial data on tissue protein expression. This 'evolutionary gap' between conventional and next-generation IHC can be filled by comprehensive IHC based on digital technologies (empowered by quantification and spatial and multiparametric analytics) and integrated into the pathology workflow and information systems. In this paper, we share our perspectives on a comprehensive IHC road map as a multistep development process.

Neoadjuvant Treatment Approach: The Rosetta Stone for Breast Cancer?

Breast cancer represents a heterogeneous group of diseases with varied biological features, behavior, and response to therapy; thus, management of breast cancer relies on the availability of robust predictive and prognostic factors to support therapy decision-making. Traditionally, neoadjuvant treatment for breast cancer was preserved for locally advanced, converting an inoperable to a surgical resectable cancer. Neoadjuvant trials, additionally, offer: 1) the opportunity to evaluate new treatment options in a faster way and with fewer patients than large adjuvant trials; 2) to identify and validate the prognostic and predictive value of a marker with its association with clinical outcome in relation to the administered treatment. In this setting, thanks to new, affordable technologies which help to detail the molecular profiles of tumors, new trial designs based on new target therapies, like window-of-opportunity, are also suggested, as they represent the chance to identify tumor sensitivity or to overcome tumor resistance to the treatment used, based on its interaction with tumor biology in early tumor stages. However, clinicians and researchers should pay particular attention: In this setting, the safety of patients is paramount, given the exposure of potentially curable patients to investigational agents with limited safety experience, the definition of the study population and the study design, such as adaptive strategies, should limit patient exposure to ineffective agents, and intensify safety monitoring in the course of the treatment. Here, issues related to outcome determination in breast cancer, including some critical points of view, are presented.

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example

BACKGROUND

Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches.

METHODS AND FINDINGS

Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived.

CONCLUSIONS

The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases.

Low Concordance between Gene Expression Signatures in ER Positive HER2 Negative Breast Carcinoma Could Impair Their Clinical Application

BACKGROUND

Numerous prognostic gene expression signatures have been recently described. Among the signatures there is variation in the constituent genes that are utilized. We aim to evaluate prognostic concordance among eight gene expression signatures, on a large dataset of ER positive HER2 negative breast cancers.

METHODS

We analysed the performance of eight gene expression signatures on six different datasets of ER+ HER2- breast cancers. Survival analyses were performed using the Kaplan-Meier estimate of survival function. We assessed discrimination and concordance between the 8 signatures on survival and recurrence rates The Nottingham Prognostic Index (NPI) was used to to stratify the risk of recurrence/death.

RESULTS

The discrimination ability of the whole signatures, showed fair discrimination performances, with AUC ranging from 0.64 (95%CI 0.55-0.73 for the 76-genes signatures, to 0.72 (95%CI 0.64-0.8) for the Molecular Prognosis Index T17. Low concordance was found in predicting events in the intermediate and high-risk group, as defined by the NPI. Low risk group was the only subgroup with a good signatures concordance.

CONCLUSION

Genomic signatures may be a good option to predict prognosis as most of them perform well at the population level. They exhibit, however, a high degree of discordance in the intermediate and high-risk groups. The major benefit that we could expect from gene expression signatures is the standardization of proliferation assessment.

Patterns in target-directed breast cancer research

We undertake an analysis of ongoing BC targeted therapy trials registered to CT.gov to describe patterns of ongoing clinical research, highlight gaps in current research programs and identify ways of optimizing ongoing initiatives. A search of clinicaltrials.gov was conducted on September 4, 2013 to identify ongoing randomized phase II and III trials of targeted therapies in BC. A total of 280 trials were analyzed, the majority conducted in either human epidermal growth factor receptor 2 (HER2)-positive (n = 79, 28.2 %) or hormone receptor (HR)-positive (n = 104, 37.1 %) populations. Less than half of all trials were conducted in populations selected to match the agent under investigation (n = 126, 45 %). HER2-directed therapy is the single most investigated class of targeted agents (n = 73, 26.1 %), but trials investigating anti-angiogenic agents are also common (n = 49, 17.5 %). The most common new classes of agents under investigation in HR-positive and triple negative (TN)/BRCA-positive disease, are non-receptor protein kinase-inhibitors (n = 12; 11.5 %) and poly (ADP-ribose) polymerase inhibitors (n = 6; 30 %), respectively. The majority of regimens combine new targeted agents with either chemotherapy (n = 164, 58.6 %) or endocrine therapy (n = 113, 40.4 %); a total of 8 trials (2.8 %) investigated peptide-drug conjugates. The most frequently utilized end-points were pathological complete response in the neo-adjuvant setting (n = 36, 52.9 %) and time-to-event end-points in the adjuvant and advanced settings (77.3 and 72.6 %, respectively). Our findings suggest a need for more target-matched agent development, maintenance of a value-based focus in research and a need for the clinical development of agents to treat TN/BRCA-positive and HR-positive BC.

Risk of recurrence estimates with IHC4+C are tolerant of variations in staining and scoring: an analytical validity study

AIMS

The IHC4+C score combines assessment of oestrogen receptor (ER), progesterone receptor (PgR), HER2 and Ki67 with clinicopathological parameters to identify the risk of distant disease recurrence in patients with breast cancer, so, aiding treatment decision-making on adjuvant chemotherapy. Despite low cost and wide availability, the reported use of IHC4+C remains limited; one explanation for this is the perception that immunohistochemistry (IHC)-based methods and assessment of them lack precision, reproducibility and portability. We examined the effects of decentralised testing and easily reproducible estimate-based scoring methods on IHC4+C scores to determine its suitability for wider adoption.

METHODS

Sections from a breast cancer tissue micro-array (TMA) were distributed to three centres undertaking diagnostic breast cancer IHC. Centres stained sections using their standard procedures, and returned them for central assessment. The results were compared with those obtained at IHC4+C's originating hospital (Royal Marsden Hospital (RMH)). In parallel, TMA sections stained at RMH were scored by a variety of simplified non-counting-based methods. The results were compared with those produced using counting.

RESULTS

There was a high degree of correlation between individual IHC results produced by external centres and those of RMH (r: 0.797-0.982), and between risk of distant recurrence scores derived from them (r: 0.972-0.984). Scoring methods for ER and PgR could be adapted to require less precision without significantly affecting correlation with counted results (r: 0.933 and 0.980, respectively), but correlation between estimating and counting for Ki67 was poorer (r: 0.855).

CONCLUSIONS

IHC4+C is tolerant of variation in staining and scoring methods. Although additional confirmatory comparative studies are required, these data support use of IHC4+C in clinical practice outside RMH.

Correlation of clinicopathological outcomes with changes in IHC4 status after NACT in locally advanced breast cancers: do pre-NACT ER/PR status act as better prognosticators?

Background

Following neoadjuvant chemotherapy (NACT) for breast cancer, changes in estrogen receptor (ER), progesterone receptor (PR), HER2 status, and Ki-67 index (IHC4 status) and its correlation with pathological complete response (pCR) or relapse-free survival (RFS) rates could lead to better understanding of tumor management.

Patients and methods

Pre- and post-NACT IHC4 status and its changes were analyzed in 156 patients with breast cancer. Associations between pCR, RFS rates to IHC4 status pre- and post-NACT were investigated.

Results

pCR was found in 25.3% patients. Both ER and PR positive tumors had the lowest (14.3%) pCR compared to ER and PR negative (29%) or either ER-/PR-positive (38.6%) tumors. PR positivity was significantly associated with less likelihood of pCR (15% versus 34%). The pCR rate was low for luminal A subtype (13.68%) compared to 24.36%, 26.31%, and 33.33% for luminal B, HER2-enriched, and triple-negative subtypes, respectively. There was significant reduction in ER expression and Ki-67 index post-NACT. RFS of patients in whom the hormonal status changed from positive to negative was better compared to those of patients in whom the hormonal status changed from negative to positive.

Conclusion

Although changes in IHC4 occurred post-NACT, pre-NACT hazard ratio status prognosticated RFS better. pCR and RFS rates were lower in PR-positive tumors.

Practical issues concerning the implementation of Ki-67 proliferative index measurement in breast cancer reporting

Commercial molecular tests which rely heavily on proliferation markers to stratify breast cancer are in increasing demand, but are expensive and not widely available. There is heightened interest in the use of Ki-67 immunohistochemistry as a marker of proliferation. This study sought to examine practical issues in the incorporation of Ki-67 measurement into breast cancer reporting.We conducted a prospective study of Ki-67 proliferative activity in 85 breast carcinomas in 70 patients. We considered whether dual staining with cytokeratin and Ki-67 was necessary to exclude background cells in automated digital image analysis (DIA) and how well a semi-quantitative assessment (SQA) method of Ki-67 proliferation and formal manual counting by two pathologists correlated with DIA.Our study showed good correlation between single and dual stained specimens by DIA (Spearman correlation coefficient 0.8), with a kappa statistic of 0.51 (moderate agreement) but with significantly fewer positive cells identified in dual stained sections. There was fair correlation between SQA and DIA by two pathologists (Spearman correlation coefficient 0.7 and 0.7). Using a ≥10% cut-off to define cases with a 'low' and 'high' proliferative index gave a kappa statistic of 0.25 and 0.32 (fair agreement). There was fair correlation between formal manual counts between two pathologists (Spearman correlation coefficient 0.7; kappa 0.32). Repeat DIA on all cases showed excellent correlation (Spearman coefficient 0.98; kappa 1.0).Automated digital analysis of Ki-67 PI is likely to be more accurate and consistent than semi-quantitative assessment and more practicable than formal manual counting. There remain challenges in standardisation of technique within and across laboratories, interpretation of results and in evaluating clinical relevance.

Clinical utility of the IHC4+C score in oestrogen receptor-positive early breast cancer: a prospective decision impact study

BACKGROUND

Most oestrogen receptor (ER)-positive early breast cancer diagnosed today is highly curable with multimodality treatment. Systemic adjuvant treatments including endocrine therapy and chemotherapy have made a significant contribution to the increasing cure rates over the past three decades. However not all women will require chemotherapy. The IHC4+C score is a prognostic tool that integrates four immunohistochemical measures with clinicopathological features to estimate the residual risk of distant recurrence at 10 years in post-menopausal women with ER-positive breast cancer who have received 5 years of endocrine therapy. Retrospective studies indicate that the test can identify a set of women that are at such low risk of recurrence that chemotherapy can be of little benefit.

METHODS

In this study, 124 patients were prospectively selected from the multidisciplinary team meeting between January 2013 and April 2014 for IHC4+C testing. Adjuvant systemic treatment recommendations by clinicians were recorded without and with the availability of the score in addition to the patient's decision.

RESULTS

There was concordance in the MDT's recommendation without and with the availability of the score in 73% of cases. Clinicians recommended chemotherapy or at least its discussion to 74 (59%) patients, which fell to 32 (34%) patients after the IHC4+C score was made available, sparing one in four tested patients a chemotherapy recommendation, along with its toxicity and expense.

CONCLUSION

This decision impact study shows that when used by clinicians in the multidisciplinary team meeting for adjuvant decision-making, a significant proportion of patients are spared chemotherapy recommendations.

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.

Advances in the Molecular Analysis of Breast Cancer: Pathway toward Personalized Medicine

Background

Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death.

Methods

A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer.

Results

During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life.

Conclusions

This review highlights what pathologists need to know about current molecular tests for classification and prognostic/predictive assessment of breast carcinoma as well as their role as part of the medical team.

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.

Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models

Background:

Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level.

Methods:

We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction.

Results:

Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95% CI 0.71–0.77) for the Cancermath.net model and 0.72 (95% CI 0.69–0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90% with a median score dispersion at 0.08 (range 0.06–0.10). Dispersion, however, reached 30% for the subgroups with a predicted survival between 10 and 50%.

Conclusion:

This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups.

Pathologic diagnosis, immunohistochemistry, multigene assays and breast cancer treatment: progress toward "precision" cancer therapy

Clinical decisions regarding the suitability of adjuvant systemic therapy for individual patients with breast cancer depends on comprehensive assessment of the underlying biology of each patient's tumor. The previous clinical-pathologic paradigm for treatment, which had been used for decades, now has been augmented by significant advances in molecular analysis of breast tumor tissue samples. Molecular testing has the potential to understand better both tumor biology and clinical behavior, which enables more appropriate therapy choices to be made. We review the rapid evolution in profiling breast cancer tissues, and discuss the current evidence for clinical use of this information and how the emerging molecular paradigm can be integrated into the clinical-pathologic context as we progress toward "precision" therapy for patients with breast cancer and other solid tumors.

Time dependence of biomarkers: non-proportional effects of immunohistochemical panels predicting relapse risk in early breast cancer

Background:

We investigated the impact of follow-up duration to determine whether two immunohistochemical prognostic panels, IHC4 and Mammostrat, provide information on the risk of early or late distant recurrence using the Edinburgh Breast Conservation Series and the Tamoxifen vs Exemestane Adjuvant Multinational (TEAM) trial.

Methods:

The multivariable fractional polynomial time (MFPT) algorithm was used to determine which variables had possible non-proportional effects. The performance of the scores was assessed at various lengths of follow-up and Cox regression modelling was performed over the intervals of 0–5 years and >5 years.

Results:

We observed a strong time dependence of both the IHC4 and Mammostrat scores, with their effects decreasing over time. In the first 5 years of follow-up only, the addition of both scores to clinical factors provided statistically significant information (P<0.05), with increases in R² between 5 and 6% and increases in D-statistic between 0.16 and 0.21.

Conclusions:

Our analyses confirm that the IHC4 and Mammostrat scores are strong prognostic factors for time to distant recurrence but this is restricted to the first 5 years after diagnosis. This provides evidence for their combined use to predict early recurrence events in order to select those patients who may/will benefit from adjuvant chemotherapy.

Assessment of the Ki67 labeling index: a Japanese validation ring study

BACKGROUND

A lack of consistent methods to evaluate Ki67 expression is problematic in terms of accurately predicting prognosis in breast cancer. Accordingly, this study aimed to identify the causes of discrepancies in Ki67 labeling index measurements by different observers under different conditions using breast cancer samples.

PATIENTS AND METHODS

This Japanese study group compared and assessed immunohistochemical (IHC) analysis of the Ki67 labeling index when measured by different pathologists. Six pathologists (pathologists A-F) in Japan participated in this ring study. One hundred and ten surgical cases of estrogen receptor-positive and human epidermal growth factor receptor 2-negative invasive breast cancer treated in 2007 were identified from the breast cancer database of Tokai University Hospital and were included in this study.

RESULTS

For all 6 pathologists, the Ki67 labeling index were significantly different between grade 3 and grade 1 cases and between grade 3 and grade 2 cases, whereas the index tended to be different between grade 1 and grade 2 cases. Further, the Ki67 labeling indexes measured by the 6 pathologists were strongly correlated (ρ: 0.73-0.88). The IHC scores recorded by pathologist A were in moderate to good agreement with those recorded by the others in patients with a Ki67 labeling index of <13.25 % and in those with a Ki67 labeling index of >13.25 % (κ = 0.429-0.660). The Ki67 low and high concordance rates between pathologist A and the others were 0.452-0.778 and 0.862-0.979, respectively. The most pertinent reason for discrepancy in scores seemed to be the selection of the area for counting and the quality of nuclear staining.

CONCLUSION

The Ki67 labeling index measured by 6 pathologists without method standardization was in fair to good agreement. We plan to undertake a second ring study, pending recommendations by the international Ki67 panel.

Genomic instability: a stronger prognostic marker than proliferation for early stage luminal breast carcinomas

BACKGROUND

The accurate prognosis definition to tailor treatment for early luminal invasive breast carcinoma patients remains challenging.

MATERIALS AND METHODS

Two hundred fourteen early luminal breast carcinomas were genotyped with single nucleotide polymorphisms (SNPs) array to determine the number of chromosomal breakpoints as a marker of genomic instability. Proliferation was assessed by KI67 (immunohistochemistry) and genomic grade index (transcriptomic analysis). IHC3 (IHC4 score for HER2 negative tumors) was also determined.

RESULTS

In the training set (109 cases), the optimal cut-off was 34 breakpoints with a specificity of 0.94 and a sensitivity of 0.57 (Area under the curve (AUC): 0.81[0.71; 0.91]). In the validation set (105 cases), the outcome of patients with > 34 breakpoints (11 events / 22 patients) was poorer (logrank test p < 0.001; Relative Risk (RR): 3.7 [1.73; 7.92]), than that of patients with < 34 breakpoints (19 events / 83 patients).Whereas genomic grade and KI67 had a significant prognostic value in univariate analysis in contrast to IHC3 that failed to have a statistical significant prognostic value in this series, the number of breakpoints remained the only significant parameter predictive of outcome (RR: 3.47, Confidence Interval (CI [1.29; 9.31], p = 0.014)) in multivariate analysis .

CONCLUSION

Genomic instability, defined herein as a high number of chromosomal breakpoints, in early stage luminal breast carcinoma is a stronger prognostic marker than proliferation.

Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility

Gene signatures which are based on multigene profiling assays have been developed for the purpose to better define the prognosis and prediction of therapy results in early-stage breast cancer. These assays were designed to be more specific than conventional clinico-pathologic parameters in the selection of patients for (neo-)adjuvant treatment and in effect help to avoid unnecessary cytotoxic treatment. In this review we describe molecular risk scores, for which tests are commercially available (PAM50®, MammaTyper®, MammaPrint®, Oncotype DX®, Endopredict®, Genomic Grade Index®) and IHC risk scores (Mammostrat® and IHC4), and discuss the current evidence of their clinical use.

Interobserver concordance in implementing the 2010 ASCO/CAP recommendations for reporting ER in breast carcinomas: a demonstration of the difficulties of consistently reporting low levels of ER expression by manual quantification

OBJECTIVES

Endocrine therapy reduces recurrence risk by 30% to 50% in estrogen receptor (ER)-positive breast cancer. The ER-positive threshold recommended by the American Society of Clinical Oncology/College of American Pathologists is 1% based on studies using the ER-6F11 antibody. ER-SP1 antibody has a higher sensitivity and is more widely used.

METHODS

We report interobserver concordance manually measuring ER in 264 breast cancers using ER-SP1 and 1D5 and 2 scoring methods (H-score and Allred score).

RESULTS

With both antibodies, 3% to 4% of cases have a low level of ER expression (1%-10%), more than previously reported (<1%). We find a high level of paired observer concordance with both antibodies and scoring methods (κ = 0.892-0.943) with no significant difference with method of scoring. Despite excellent concordance, positive/negative discordance was almost 5% among 3 observers using either antibody, an underappreciated clinically significant rate.

CONCLUSIONS

Discordance overwhelmingly reflected differing opinions recording the proportion of tumor cells positive with low levels of expression (<10% staining; 12/13 cases).

Molecular and protein markers for clinical decision making in breast cancer: today and tomorrow

In early breast cancer (eBC), established clinicopathological factors are not sufficient for clinical decision making particularly regarding adjuvant chemotherapy since substantial over- or undertreatment may occur. Thus, novel protein- and molecular markers have been put forward as decision aids. Since these potential prognosis and/or predictive tests differ substantially regarding their methodology, analytical and clinical validation, this review attempts to summarize the essential facts for clinicians. This review focuses on those markers which are the most advanced so far in their development towards routine clinical application, i.e. two protein markers (i.e. uPA/PAI-1 and IHC4) and six molecular multigene tests (i.e. Mammaprint®, Oncotype DX®, PAM50, Endopredict®, the 97-gene genomic grade, and 76 gene Rotterdam signatures). Next to methodological aspects, we summarized the clinical evidences, in particular the main prospective clinical trials which have already been fully recruited (i.e. MINDACT, TAILORx, WSG PLAN B) or are still ongoing (i.e. RxPONDER/SWOG S1007, WSG-ADAPT). Last but not least, this review points out the key elements for clinicians to select one test among the wide panel of proposed assays, for a specific population of patients in term of level of evidence, analytical and clinical validity as well as cost effectiveness.

Intrinsic breast cancer subtypes defined by estrogen receptor signalling-prognostic relevance of progesterone receptor loss

The majority of luminal type breast carcinomas are slowly growing tumors with an overall favorable prognosis. However, a proportion of cases (luminal B tumors) are characterized by coactivation of growth factor receptors or non-canonical ER signaling and a poorer clinical outcome. The aim of our study was to evaluate whether the expression of proteins that are part of the ER signaling network may be used to distinguish low-risk from high-risk luminal tumors. Unsupervised hierarchical clustering of a set of proteins either involved in estrogen receptor signaling or associated with resistance to endocrine therapy was performed in a series of 443 postmenopausal breast carcinomas. Using this approach, we were able to reproduce the established classification with two distinct groups of luminal (estrogen receptor positive) tumors, one group of HER2-associated tumors and a group of triple-negative tumors. However, neither proliferation nor the expression of one or more of the ER-co-factors or resistance-associated factors, but PR-expression was identified as the most important stratifier distinguishing between the two luminal groups. In fact, not only the four identified clusters were shown to be significantly associated with patient outcome, PR-expression alone or in combination with Ki-67-stains stratified ER-positive tumors into a low-risk and a high-risk group. Our data indicate that defining luminal B tumors by the presence of high-risk criteria (loss of PR-expression or increased proliferation) provides a robust and highly significant stratification of ER-positive breast carcinomas into luminal A and B.

Immunohistochemical BAG1 expression improves the estimation of residual risk by IHC4 in postmenopausal patients treated with anastrazole or tamoxifen: a TransATAC study

BAG1 is a multifunctional anti-apoptotic protein located on chromosome 9q12, which binds to Bcl-2. BAG1 is present as a separate module in the GHI-RS 21-gene panel. It may provide additional prognostic information as an immunohistochemical marker when added to IHC4. Analysis of BAG1 was performed on archival tumour blocks from patients from the anastrozole and tamoxifen arms of the ATAC trial of 5 years endocrine therapy in postmenopausal women with oestrogen receptor (ER)-positive primary breast cancer. Staining was scored separately as nuclear or cytoplasmic. Statistical analyses were performed on data from median 10-year follow-up with distant recurrence as primary endpoint. Data on both nuclear and cytoplasmic BAG1 as well as the IHC4 markers (ER, PgR, HER2 and Ki67) were available on 963 ER-positive cases of which 860 were HER2-negative. Cytoplasmic and nuclear BAG1 were highly correlated (Spearman r = 0.79, p < 00001). Women with higher BAG1 expression developed 30 % fewer distant recurrences compared to those with low expression. Nuclear BAG1 contributed significantly to the clinical and IHC4 models with added information being greater in node-positive cases. Similar results were seen if all recurrences were the endpoints. BAG1 expression provides significant prognostic information when added to the classical clinicopathological parameters and IHC4, particularly in node-positive patients.

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

Background

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

Methodology/Principal Findings

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

Conclusions/Significance

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

Modern Risk Assessment for Individualizing Treatment Concepts in Early-stage Breast Cancer

Validated prognostic and predictive factors currently play an important role in treatment planning for patients with early-stage breast cancer. The role of personalized medicine has led to the search for markers that can be applied to individual patients to optimize treatment regimens. In addition to traditional clinicopathologic measures, scores and gene tests have been developed to independently predict risk of patients in the neoadjuvant and adjuvant settings. The discovery of these markers provides the opportunity to identify patients at such low risk of recurrence that toxic therapy side effects are not justified. Selection and management of patients with early-stage, hormone receptor-positive breast cancer who are appropriately treated with endocrine therapy alone after receiving locoregional therapy but do not necessarily require adjuvant chemotherapy is currently problematic. This article reviews the current state-of-theart biomarker assessment methods and discusses the potential role for the prediction of chemotherapy benefit focusing on endocrine sensitive disease.