Prognostic and predictive indicators in early-stage breast cancer and the role of genomic profiling: Focus on the Oncotype DX ® Breast Recurrence Score Assay

Validation of the AJCC 8th Edition Breast Cancer Prognostic Staging System in Legacy Alliance Trials (AFT-01)

BACKGROUND

The 8th edition American Joint Committee on Cancer staging system combined anatomic stage (AS) with receptor status and grade to create prognostic stage (PS). PS has been validated in single-institution and cancer registry studies; however, missing human epidermal growth factor receptor 2 (HER2) status and variable treatment and follow-up create limitations.

OBJECTIVE

Our objective was to compare the relative prognostic ability of PS versus AS to predict survival using breast cancer clinical trial data.

METHODS

Women with non-metastatic breast cancer enrolled in six Alliance for Clinical Trials in Oncology trials were included (enrollment years 1997-2010). AS and PS were constructed using pathological tumor size, nodal status, estrogen receptor (ER), progesterone receptor (PR), HER2 status, and grade. Unadjusted Cox proportional hazard models were estimated to predict overall survival within 5 years, with AS and PS as predictor variables. The relative predictive power of staging models was assessed by comparing Harrell concordance indices (C-indices). Kaplan-Meier-based mortality estimates were compared by stage.

RESULTS

Overall, 6924 women were included (median age 53 years); 45.2% were diagnosed with ER+/PR+/HER2- tumors, 26.2% with HER2+ tumors, and 17.1% with ER-/PR-/HER2- tumors. Median follow-up time was 5 years (interquartile range 2.95-5.00). PS significantly improved predictive performance (C-index 0.721) for overall survival compared with AS (0.700) (p = 0.020). Kaplan-Meier hazard estimates suggested PS did not distinguish mortality risk between patients with IIB and IIIA or IB and IIA disease.

CONCLUSIONS

PS has significantly improved predictive performance for OS compared with AS. As systemic therapies evolve, it will be important to re-evaluate the prognostic staging system, particularly for patients with intermediate-stage cancers.

CLINICALTRIALS

gov Identifier: NCT02171078.

Low correlation between Ki67 assessed by qRT-PCR in Oncotype Dx score and Ki67 assessed by Immunohistochemistry

Breast cancers expressing high levels of Ki67 are associated with poor outcomes. Oncotype DX test was designed for ER+/HER2- early-stage breast cancers to help adjuvant chemotherapy decision by providing a Recurrent Score (RS). RS measures the expression of 21 specific genes from tumor tissue, including Ki67. The primary aim of this study was to assess the agreement between Ki67_RNA obtained with Oncotype DX RS and Ki67_IHC. Other objectives were to analyze the association between the event free survival (EFS) and the expression level of Ki67_RNA; and association between RS and Ki67_RNA. Herein, we report a low agreement of 0.288 by Pearson correlation coefficient test between Ki67_IHC and Ki67_RNA in a cohort of 98 patients with early ER+/HER2- breast cancers. Moreover, Ki67_RNA^high tumors were significantly associated with the occurrence of events (p = 0.03). On the other hand, we did not find any association between Ki67_IHC and EFS (p = 0.26). We observed a low agreement between expression level of Ki67_RNA and Ki67 protein labelling by IHC. Unlike Ki67_IHC and independently of the RS, Ki67_RNA could have a prognostic value. It would be interesting to better assess the prognosis and predictive value of Ki67_RNA measured by qRT-PCR. The Ki67_RNA in medical routine could be a good support in countries where Oncotype DX is not accessible.

Preoperative Systemic Inflammatory Biomarkers Are Independent Predictors of Disease Recurrence in ER+ HER2- Early Breast Cancer

The host's immune system plays a crucial role in determining the clinical outcome of many cancers, including breast cancer. Peripheral blood neutrophils and lymphocytes counts may be surrogate markers of systemic inflammation and potentially reflect survival outcomes. The aim of the present study is to assess the role of preoperative systemic inflammatory biomarkers to predict local or distant relapse in breast cancer. In particular we investigated ER+ HER2- early breast cancer, considering its challenging risk stratification. A total of 1,763 breast cancer patients treated at tertiary referral Breast Unit were reviewed. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR) and lymphocyte-to-monocyte (LMR) ratios were assessed from the preoperative blood counts. Multivariate analyses for 5-years locoregional recurrence-free (LRRFS), distant metastases-free (DMFS) and disease-free survivals (DFS) were performed, taking into account both blood inflammatory biomarkers and clinical-pathological variables. Low NLR and high LMR were independent predictors of longer LRRFS, DMFS and DFS, and low PLR was predictive of better LRRFS and DMFS in the study population. In 999 ER+ HER2- early breast cancers, high PLR was predictive of worse LRRFS (HR 0.42, p=0.009), while high LMR was predictive of improved LRRFS (HR 2.20, p=0.02) and DFS (HR 2.10, p=0.01). NLR was not an independent factor of 5-years survival in this patients' subset. Inflammatory blood biomarkers and current clinical assessment of the disease were not in agreement in terms of estimate of relapse risk (K-Cohen from -0.03 to 0.02). In conclusion, preoperative lymphocyte ratios, in particular PLR and LMR, showed prognostic relevance in ER+ HER2- early breast cancer. Therefore, they may be used in risk stratification and therapy escalation/de-escalation in patients with this type of tumor.

Hereditary Breast and Ovarian Cancer Screening Syndrome Profile in Women Diagnosed with Breast Cancer from Paraná State Southwest

OBJECTIVE

 This study evaluated the risk of the hereditary breast and ovarian cancer (HBOC) syndrome in patients with breast cancer by using the Family History Screening 7 (FHS-7) tool, a validated low-cost questionnaire with high sensitivity able to screen the HBOC risk in the population.

METHODS

 Women diagnosed with breast cancer (n = 101) assisted by the Unified Health System at the 8th Regional Health Municipal Office of the state of Paraná answered the FHS-7, and the results were analyzed using IBM SPSS Statistics for Windows, Version 25.0. software (IBM Corp., Armonk, NY, USA).

RESULTS

 The risk of HBOC was 19.80% (n = 20). Patients at risk exhibited aggressive tumor characteristics, such as high-grade tumors (30%), presence of angiolymphatic emboli (35%), and premenopausal at diagnosis (50%). Significant associations between the prevalence of high-grade tumors were observed in women younger than 50 years at diagnosis with HBOC (p = 0.003).

CONCLUSION

 Our findings suggest a possible family inheritance associated with worse clinical features in women with breast cancer in this population, indicating that HBOC investigation can be initially performed with low-cost instruments such as FHS-7.

The impact of endogenous estrogen exposures on the characteristics and outcomes of estrogen receptor positive, early breast cancer

BACKGROUND

Menstrual and parity history might impact the risk for breast cancer. Data on the impact of these factors on other tumor characteristics are limited.

METHODS

A single center retrospective cohort study comprising all women with estrogen receptor (ER) positive, human epidermal growth factor receptor 2 (HER2) negative, early breast cancer whose tumors were sent to OncotypeDX analysis. The prespecified subgroups were investigated: age of menarche (< 12 vs. ≥ 12 years), number of deliveries (0 vs. ≥ 1 childbirth and ≥ 5 childbirth vs. other), age of first delivery (≥ 30 years vs. younger age) and postmenopausal compared to premenopausal. The impact of age of menopause was also assessed categorically, using early (< 45 years) and late age of menopause (> 55 years). Differences in tumor characteristics were evaluated using T-test or Mann Whitney for continuous variables or Fisher's exact test for categorical variables. Outcomes were assessed by Kaplan-Meier survival analysis, with the log-rank test.

RESULTS

A total of 620 women were included. After median follow-up of 10.4 years, early menopause was associated with significantly worse disease-free survival (HR = 2.26, p = 0.004) and overall-survival (HR = 2.60, p = 0.004), and multiparity was associated with significant worse disease-free survival (HR = 2.16, p = 0.026). These differences remain significant in multivariate analyses. Post-menopausal women were more likely to have stronger ER intensity (p = 0.002) but progesterone receptor (PR) positivity was less frequent (p = 0.009(. Early age of menarche was associated with PR positivity (p = 0.039). No other associations were found between the evaluated subgroups and tumor characteristics.

CONCLUSIONS

The impact of endogenous estrogen exposure had little effect on breast cancer characteristics of early stage, luminal disease. Early menopause and multiparity were associated with worse outcome.

Efficacy of adjuvant chemotherapy stratified by age and the 21-gene recurrence score in estrogen receptor-positive breast cancer

BACKGROUND

The 21-gene recurrence score (RS) can predict chemotherapy benefit in estrogen receptor-positive, human epidermal growth factor receptor-2-negative (ER+/HER2-) early breast cancer patients. Age would influence the interaction between RS and chemotherapy effect. The current study aimed to determine RS thresholds which were predictive of chemotherapy benefit in young and old women, respectively.

METHODS

Patients diagnosed with pN0-1, ER+/HER2- breast cancer between 2009 and 2016 were retrospectively reviewed. Propensity score matching was performed according to chemotherapy usage. After stratifying patients with different cutoffs of age, the RS threshold indicating chemotherapy benefit in each age strata were determined by cox proportional hazard models.

RESULTS

A total of 1227 patients were included. The median age was 58 years and the median RS was 24. After matching, the RS thresholds suggesting chemotherapy benefit varied with age. For patients ≤55 years, chemotherapy benefit was observed in those having RS > 25 (P = 0.03), with 4-year invasive disease-free survival (IDFS) of 97.0 and 89.3% in patients receiving chemotherapy or not. While patients derived no benefit from chemotherapy if they had RS ≤25 (P = 0.66, 4-year IDFS: 95.3% vs. 94.6%). For patients > 55 years, adjuvant chemotherapy was associated with better prognosis in those with RS > 36 (P = 0.014, 4-year IDFS: 94.7% vs. 76.2%), but not in those having RS ≤36 (P = 0.13, 4-year IDFS: 92.3% vs. 95.8%).

CONCLUSIONS

Old patients need higher RS thresholds to demonstrate the chemotherapy benefit. Further efforts are warranted to investigate the association between age and predictive RS thresholds.

Quantitative assessment of distant recurrence risk in early stage breast cancer using a nonlinear combination of pathological, clinical and imaging variables

Use of genomic assays to determine distant recurrence risk in patients with early stage breast cancer has expanded and is now included in the American Joint Committee on Cancer staging manual. Algorithmic alternatives using standard clinical and pathology information may provide equivalent benefit in settings where genomic tests, such as OncotypeDx, are unavailable. We developed an artificial neural network (ANN) model to nonlinearly estimate risk of distant cancer recurrence. In addition to clinical and pathological variables, we enhanced our model using intraoperatively determined global mammographic breast density (MBD) and local breast density (LBD). LBD was measured with optical spectral imaging capable of sensing regional concentrations of tissue constituents. A cohort of 56 ER+ patients with an OncotypeDx score was evaluated. We demonstrated that combining MBD/LBD measurements with clinical and pathological variables improves distant recurrence risk prediction accuracy, with high correlation (r = 0.98) to the OncotypeDx recurrence score.

Current advances in the diagnosis and personalized treatment of breast cancer: lessons from tumor biology

Breast cancer treatment has advanced enormously in the last decade. Most of this is due to advances reached in the knowledge regarding tumor biology, mainly in the field of diagnosis and treatment. This review brings information about how the genomics-based information contributed to advances in breast cancer diagnosis and prognosis perspective, as well as presents how tumor biology discoveries fostered the main therapeutic approaches available to treat such patients, based on a personalized point of view.

RDGN-based predictive model for the prognosis of breast cancer

Background

Breast cancer is the most diagnosed malignancy in females in the United States. The members of retinal determination gene network (RDGN) including DACH, EYA, as well as SIX families participate in the proliferation, apoptosis, and metastasis of multiple tumors including breast cancer. A comprehensive predictive model of RDGN might be helpful to herald the prognosis of breast cancer patients.

Methods

In this study, the Gene Expression Ominibus (GEO) and Gene Set Expression Analysis (GSEA) algorithm were used to investigate the effect of RDGN members on downstream signaling pathways. Besides, based on The Cancer Genome Atlas (TCGA) database, we explored the expression patterns of RDGN members in tumors, normal tissues, and different breast cancer subtypes. Moreover, we estimated the relationship between RDGN members and the outcomes of breast cancer patients. Lastly, we constructed a RDGN-based predictive model by Cox proportional hazard regression and verified the model in two separate GEO datasets.

Results

The results of GSEA showed that the expression of DACH1 was negatively correlated with cell cycle and DNA replication pathways. On the contrary, the levels of EYA2 and SIX1 were significantly positively correlated with DNA replication, mTOR, and Wnt pathways. Further investigation in TCGA database indicated that DACH1 expression was lower in breast cancers especially basal-like subtype. In the meanwhile, SIX1 was remarkably upregulated in breast cancers while EYA2 level was increased in Basal-like and Her-2 enriched subtypes. Survival analyses demonstrated that DACH1 was a favorable factor while EYA2 and SIX1 were risk factors for breast cancer patients. Given the results of Cox proportional hazard regression analysis, two members of RDGN were involved in the present predictive model and patients with high model index had poorer outcomes.

Conclusion

This study showed that aberrant RDGN expression was an unfavorable factor for breast cancer. This RDGN-based comprehensively framework was meaningful for predicting the prognosis of breast cancer patients.

Machine Learning techniques in breast cancer prognosis prediction: A primary evaluation

More than 750 000 women in Italy are surviving a diagnosis of breast cancer. A large body of literature tells us which characteristics impact the most on their prognosis. However, the prediction of each disease course and then the establishment of a therapeutic plan and follow‐up tailored to the patient is still very complicated. In order to address this issue, a multidisciplinary approach has become widely accepted, while the Multigene Signature Panels and the Nottingham Prognostic Index are still discussed options. The current technological resources permit to gather many data for each patient. Machine Learning (ML) allows us to draw on these data, to discover their mutual relations and to esteem the prognosis for the new instances. This study provides a primary evaluation of the application of ML to predict breast cancer prognosis. We analyzed 1021 patients who underwent surgery for breast cancer in our Institute and we included 610 of them. Three outcomes were chosen: cancer recurrence (both loco‐regional and systemic) and death from the disease within 32 months. We developed two types of ML models for every outcome (Artificial Neural Network and Support Vector Machine). Each ML algorithm was tested in accuracy (=95.29%‐96.86%), sensitivity (=0.35‐0.64), specificity (=0.97‐0.99), and AUC (=0.804‐0.916). These models might become an additional resource to evaluate the prognosis of breast cancer patients in our daily clinical practice. Before that, we should increase their sensitivity, according to literature, by considering a wider population sample with a longer period of follow‐up. However, specificity, accuracy, minimal additional costs, and reproducibility are already encouraging.

Results of PONDx, a prospective multicenter study of the Oncotype DX® breast cancer assay: Real-life utilization and decision impact in French clinical practice

Adjuvant chemotherapy shows clear benefits in HER2-positive and triple-negative breast cancer (BC). Its benefits are less universal in BCs expressing hormone receptors. The 21-gene Oncotype DX^® Breast Recurrence Score test was designed for HR+, HER2- early-stage BC before decision on adjuvant chemotherapy. Its validity and utility was demonstrated prospectively across multiple studies. The observational study PONDx characterized the use of Oncotype DX^® Breast in routine practice in France and evaluated its decision impact. Of 882 ER-positive BC patients (67% postmenopausal), most (79%) had N0/Nmic node involvement, grade 2 tumors (68%), tumor size 1-5 cm (88%), and ductal histology (78%). BCs with histopathologically elevated recurrence risk included grade 3: 18%; N1: 21%; Ki67 > 20%: 31%. Recurrence Score results by prognostic category were: <18: 54%, 18-30: 36%; >30: 10%. Compared to recommendations before individual availability of the score, results prompted net absolute reductions in chemotherapy recommendations of 36% (total population), and 29% (grade 3 and/or Ki67 > 20% histologies). Decisions reflected prognostic implications: in the Recurrence Score <18 category, 95% of patients received recommendations of hormonal therapy only, in the >30 category, 97.5% were recommended additional chemotherapy; 95% followed the final recommendations of their physicians. The Recurrence Score provides independent predictive and prognostic information in ER + N0/N1 early BC, including high-risk subgroups. PONDx further characterizes the population where the test is beneficial in real-life use and fits current clinical needs. Oncotype DX^® Breast enables relevant net reductions in chemotherapy use, sparing patients from serious toxicities. Its therapeutic implications are highly accepted by physicians and patients.

The Prognostic Significance of the Oncotype DX Recurrence Score in T1-2N1M0 Estrogen Receptor-Positive HER2-Negative Breast Cancer Based on the Prognostic Stage in the Updated AJCC 8th Edition

BACKGROUND

This study aimed to evaluate the prognostic significance of the Oncotype DX recurrence score (RS) in T_1-2N₁M₀ estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer based on the prognostic stage in the updated American Joint Commission on Cancer, 8th edition.

METHODS

The Surveillance, Epidemiology, and End Results database was searched to identify ER-positive invasive ductal breast cancer in T_1-2N₁M₀ with RS results diagnosed between 2004 and 2012. Patients with RS were categorized into low-risk (RS < 11), intermediate-risk (RS 11-25), and high-risk (RS > 25) groups. The distributions of clinical-pathological characteristics were compared among the RS risk groups using Pearson's Chi square. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared across RS groups using the log-rank statistic. Cox models were fitted to assess the factors independently associated with survival.

RESULTS

The study enrolled 4059 cases categorized into prognostic stages IA to IIB. The RS risk groups were positively correlated with pathological prognostic stages (P < 0.001). The RS risk groups differed significantly in terms of BCSS and OS (P < 0.001). According to the multivariate analysis, RS risk group was an independent prognostic factor for BCSS and OS together with the pathological prognostic stage. The subgroup analysis showed similar survival rates across pathological prognostic stages in the RS low-risk group but significant differences in survival rates among pathological prognostic stages in the RS intermediate-risk group. The survival rates among the RS risk groups also differed significantly in pathological prognostic stage IA.

CONCLUSIONS

Oncotype DX RS provided independent prognostic significance to complement the prognostic staging system.

Budget impact analysis of gene expression tests to aid therapy decisions for breast cancer patients in Germany

OBJECTIVES

Many women with early-stage, hormone receptor-positive breast cancer may not benefit from adjuvant chemotherapy. Gene expression tests can reduce chemotherapy over- and undertreatment by providing prognostic information on the likelihood of recurrence and, with Oncotype DX, predictive information on chemotherapy benefit. These tests are currently not reimbursed by German healthcare payers. An analysis was conducted to evaluate the budget impact of gene expression tests in Germany.

MATERIALS AND METHODS

Costs of gene expression tests and medical and non-medical costs associated with treatment were assessed from healthcare payer and societal perspectives. Costs were estimated from data collected at a university hospital and were combined with decision impact data for Oncotype DX, MammaPrint, Prosigna and EndoPredict (EPclin). Changes in chemotherapy use and budget impact were evaluated over 1 year for 20,000 women.

RESULTS

Chemotherapy was associated with substantial annual costs of EUR 19,003 and EUR 84,412 per therapy from the healthcare payer and societal perspective, respectively. Compared with standard care, only Oncotype DX was associated with cost savings to healthcare payers and society (EUR 5.9 million and EUR 253 million, respectively). Scenario analysis showed that both women at high clinical but low genomic risk and low clinical but high genomic risk were important contributors to costs.

CONCLUSIONS

Oncotype DX was the only gene expression test that was estimated to reduce costs versus standard care in Germany. The reimbursement of Oncotype DX testing in standard clinical practice in Germany should be considered.

Assessment of the prognostic role of a 94-single nucleotide polymorphisms risk score in early breast cancer in the SIGNAL/PHARE prospective cohort: no correlation with clinico-pathological characteristics and outcomes

Background

Genome-wide association studies (GWAS) have to date identified 94 genetic variants (single nucleotide polymorphisms (SNPs)) associated with risk of developing breast cancer. A score based on the combined effect of the 94 risk alleles can be calculated to measure the global risk of breast cancer. We aimed to test the hypothesis that the 94-SNP-based risk score is associated with clinico-pathological characteristics, breast cancer subtypes and outcomes in early breast cancer.

Methods

A 94-SNP risk score was calculated in 8703 patients in the PHARE and SIGNAL prospective case cohorts. This score is the total number of inherited risk alleles based on 94 selected SNPs. Clinical data and outcomes were prospectively registered. Genotyping was obtained from a GWAS.

Results

The median 94-SNP risk score in 8703 patients with early breast cancer was 77.5 (range: 58.1–97.6). The risk score was not associated with usual prognostic and predictive factors (age; tumor, node, metastasis (TNM) status; Scarff-Bloom-Richardson grade; inflammatory features; estrogen receptor status; progesterone receptor status; human epidermal growth factor receptor 2 (HER2) status) and did not correlate with breast cancer subtypes. The 94-SNP risk score did not predict outcomes represented by overall survival or disease-free survival.

Conclusions

In a prospective case cohort of 8703 patients, a risk score based on 94 SNPs was not associated with breast cancer characteristics, cancer subtypes, or patients’ outcomes. If we hypothesize that prognosis and subtypes of breast cancer are determined by constitutional genetic factors, our results suggest that a score based on breast cancer risk-associated SNPs is not associated with prognosis.

Trial registration

PHARE cohort: NCT00381901, Sept. 26, 2006 – SIGNAL cohort: INCa RECF1098, Jan. 28, 2009

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0888-4) contains supplementary material, which is available to authorized users.

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

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

The Era of Multigene Panels Comes? The Clinical Utility of Oncotype DX and MammaPrint

The AJCC Cancer Staging Manual, eighth edition published in late 2016, will become the new global guideline for cancer diagnosis and treatment from January 1, 2018. The new edition for the tumor staging system has numerous updates, including building up the prognostic stage group of tumors for the first time and adding a large number of non-anatomical factors into the prognostic evaluation. Oncotype DX and MammaPrint are two of the genomic predictors that will be part of routine clinical practice in the future. Numerous studies have proved the clinical utility of multigene panels in predicting clinical outcome and treatment response. Here we present our review of the studies on these multigene panels and their application to breast cancer.