Research-based PAM50 subtype predictor identifies higher responses and improved survival outcomes in HER2-positive breast cancer in the NOAH study

A framework for estimating and testing qualitative interactions with applications to predictive biomarkers

An effective treatment may only benefit a subset of patients enrolled in a clinical trial. We translate the search for patient characteristics that predict treatment benefit to a search for qualitative interactions, which occur when the estimated response-curve under treatment crosses the estimated response-curve under control. We propose a regression-based framework that tests for qualitative interactions without assuming linearity or requiring pre-specified risk strata; this flexibility is useful in settings where there is limited a priori scientific knowledge about the relationship between features and the response. Simulations suggest that our method controls Type I error while offering an improvement in power over a procedure based on linear regression or a procedure that pre-specifies evenly spaced risk strata. We apply our method to a publicly available dataset to search for a subset of HER2+ breast cancer patients who benefit from adjuvant chemotherapy. We implement our method in Python and share the code/data used to produce our results on GitHub (https://github.com/jhroth/data-example).

Overcoming Therapeutic Resistance of Triple Positive Breast Cancer with CDK4/6 Inhibition

Triple positive breast cancers overexpress both the human epidermal growth factor receptor 2 (HER2) oncogene and the hormonal receptors (HR) to estrogen and progesterone. These cancers represent a unique therapeutic challenge because of a bidirectional cross-talk between the estrogen receptor alpha (ERα) and HER2 pathways leading to tumor progression and resistance to targeted therapy. Attempts to combine standard of care HER2-targeted drugs with antihormonal agents for the treatment of HR+/HER2+ breast cancer yielded encouraging results in preclinical experiments but did improve overall survival in clinical trial. In this review, we dissect multiple mechanisms of therapeutic resistance typical of HR+/HER2+ breast cancer, summarize prior clinical trials of targeted agents, and describe novel rational drug combinations that include antihormonal agents, HER2-targeted drugs, and CDK4/6 inhibitors for treatment of the HR+/HER2+ breast cancer subtype.

Molecular Classification of Breast Cancer

Breast cancer is a heterogeneous disease, observed traditionally by morphology and protein expression but, more recently with the advent of modern molecular technologies, at the genomic and transcriptomic level. This review describes the association between the different molecular subtypes with the histologic subtypes of breast cancer alongside some of their major genomic characteristics and illustrates how these subtypes may affect the appearance of tumors on imaging studies. The authors aim to show how molecular stratification can be used to augment traditional methods to improve our understanding of breast cancers and their clinical management.

Clinical implications of the non-luminal intrinsic subtypes in hormone receptor-positive breast cancer

Gene expression profiling has had a considerable impact on our understanding ofbreastcancer biology. Duringthelast decade, 4 intrinsic molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched [HER2-E] and Basal-like) have been identified and intensively studied. In this article, we review and discuss the clinical implications of the 2 non-luminal subtypes (i.e. HER2-E and Basal-like) identified within hormone receptor (HR)-positive disease. After reviewing 32 studies for a total of 13,091 samples, ∼8% and ∼ 15% of early and metastatic HR+/HER2-negative breast cancer, respectively, were found to be non-luminal. Clinically, HR+/HER2-negative/non-luminal subtypes have been associated with estrogen independence, chemo-sensitivity, resistance to CDK4/6 inhibition and poor outcome. Interestingly, EGFR/HER2 tyrosine kinase inhibition might be of value in the HR+/HER2-negative/HER2-E subtype. Finally, the HER2-E subtype within HR+/HER2 + disease represents ∼ 30% and has been associated with anti-HER2 sensitivity, chemo-sensitivity and resistance to CDK4/6 inhibition. In the upcoming years, retrospective and prospective clinical trials evaluating both biomarkers should lead to improvements in patient outcomes.

PregOMICS-Leveraging systems biology and bioinformatics for drug repurposing in maternal-child health

Obstetric diseases remain underserved and understudied. Drug repurposing-utilization of a drug whose use is accepted in one condition for a different condition-could represent a rapid and low-cost way to identify new therapies that are known to be safe. In diseases of pregnancy, the known safety profile is a strong additional incentive. We describe the techniques and steps used in the use of 'omics data for drug repurposing. We illustrate these techniques using case studies of published drug repurposing projects. We provide a set of available databases with low barriers to entry which investigators can use to perform their own projects. The promise of 'omics techniques is unbiased screening, either of all drug targets or of all patients using particular drugs to find which are likely to alter disease risk or progression. However, we caution that reproducibility across the underlying studies, and thus the drugs suggested for repurposing, can be poor. We suggest that improved nosology, for example correlating patient clinical conditions with placental pathology, could yield more robust associations. We conclude that 'omics-driven drug repurposing represents a potential fruitful path to discover new, safe treatments of obstetric diseases.

Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer

Aims

The accuracy of biomarker assessment in breast pathology is vital for therapy decisions. The therapy predictive and prognostic biomarkers oestrogen receptor (ER), progesterone receptor, HER2 and Ki67 may act as surrogates to gene expression profiling of breast cancer. The aims of this study were to investigate the concordance of consecutive biomarker assessment by immunocytochemistry on preoperative fine-needle aspiration cytology versus immunohistochemistry (IHC) on the corresponding resected breast tumours. Further, to investigate the concordance with molecular subtype and correlation to stage and outcome.

Methods

Two retrospective cohorts comprising 385 breast tumours with clinicopathological data including gene expression-based subtype and up to 10-year overall survival data were evaluated.

Results

In both cohorts, we identified a substantial variation in Ki67 index between cytology and histology and a switch between low and high proliferation within the same tumour in 121/360 cases. ER evaluations were discordant in only 1.5% of the tumours. From cohort 2, gene expression data with PAM50 subtype were used to correlate surrogate subtypes. IHC-based surrogate classification could identify the correct molecular subtype in 60% and 64% of patients by cytology (n=63) and surgical resections (n=73), respectively. Furthermore, high Ki67 in surgical resections but not in cytology was associated with poor overall survival and higher probability for axillary lymph node metastasis.

Conclusions

This study shows considerable differences in the prognostic value of Ki67 but not ER in breast cancer depending on the diagnostic method. Furthermore, our findings show that both methods are insufficient in predicting true molecular subtypes.

B49, a BST-2-based peptide, inhibits adhesion and growth of breast cancer cells

Bone marrow stromal antigen 2 (BST-2) also known as Tetherin has been implicated in the growth and progression of many cancers. BST-2 employs its pro-tumor effects through the formation of BST-2:BST-2 dimers which ultimately promotes cell to cell and cell to matrix adhesion, cell motility, survival, and growth. The aim of this study was to evaluate the effect of a novel BST-2-based peptide-B49 on adhesion and growth of breast cancer cells. Homotypic/heterotypic adhesion, three-dimensional spheroid formation, and anchorage-independent growth were used to assess the effect of B49 on cell adhesion and growth. Additionally, we provide evidence of the anti-tumor effect of B49 in a preclinical mouse model of breast cancer. Results show that breast cancer cell adhesion to other cancer cells or components of the tumor microenvironment were inhibited by B49. Most well-known evaluation indexes of cancer cell growth, including spheroid formation, anchorage-independent, and primary tumor growth were significantly inhibited by B49. These data affirm that i) BST-2 plays a key role in mediating breast cancer cell adhesion and growth, and ii) B49 and its analog B49Mod1 significantly inhibits BST-2-mediated cancer cell adhesion and growth. Therefore, B49 and its analogs offer a promising anti-adhesion and therapeutic lead for BST-2-dependent cancers.

Associations between genomic stratification of breast cancer and centrally reviewed tumour pathology in the METABRIC cohort

The integration of genomic and transcriptomic profiles of 2000 breast tumours from the METABRIC [Molecular Taxonomy of Breast Cancer International Consortium] cohort revealed ten subtypes, termed integrative clusters (IntClust/s), characterised by distinct genomic drivers. Central histopathology (N = 1643) review was undertaken to explore the relationship between these ten molecular subtypes and traditional clinicopathological features. IntClust subtypes were significantly associated with histological type, tumour grade, receptor status, and lymphocytic infiltration (p < 0.0001). Lymph node status and Nottingham Prognostic Index [NPI] categories were also significantly associated with IntClust subtype. IntClust 3 was enriched for tubular and lobular carcinomas, the latter largely accounting for the association with CDH1 mutations in this cluster. Mucinous carcinomas were not present in IntClusts 5 or 10, but did not show an association with any of the remaining IntClusts. In contrast, medullary-like cancers were associated with IntClust 10 (15/26). Hormone receptor-positive tumours were scattered across all IntClusts. IntClust 5 was dominated by HER2 positivity (127/151), including both hormone receptor-positive (60/72) and hormone receptor-negative tumours (67/77). Triple-negative tumours comprised the majority of IntClust 10 (132/159) and around a quarter of IntClust 4 (52/217). Whilst the ten IntClust subtypes of breast cancer show characteristic patterns of association with traditional clinicopathological variables, no IntClust can be adequately identified by these variables alone. Hence, the addition of genomic stratification has the potential to enhance the biological relevance of the current clinical evaluation and facilitate genome-guided therapeutic strategies.

Male breast cancer: correlation between immunohistochemical subtyping and PAM50 intrinsic subtypes, and the subsequent clinical outcomes

Male breast cancer is a rare disease that is still poorly understood. It is mainly classified by immunohistochemistry as a luminal disease. In this study, we assess for the first time the correlation between molecular subtypes based on a validated six-marker immunohistochemical panel and PAM50 signature in male breast cancer, and the subsequent clinical outcome of these different subtypes. We collected 67 surgical specimens of invasive male breast cancer from four different Spanish pathology laboratories. Immunohistochemical staining for the six-marker panel was performed on tissue microarrays. PAM50 subtypes were determined in a research-use-only nCounter Analysis System. We explored the association of immunohistochemical and PAM50 subtypes. Overall survival and disease-free survival were analyzed in the different subtypes of each classification. The distribution of tumor molecular subtypes according PAM50 was: 60% luminal B, 30% luminal A and 10% human epidermal growth factor receptor 2 (Her2) enriched. Only one Her2-enriched tumor was also positive by immunohistochemistry and was treated with trastuzumab. None of the tumors were basal-like. Using immunohistochemical surrogates, 51% of the tumors were luminal B, 44% luminal A, 4% triple-negative and 1% Her2-positive. The clinicopathological characteristics did not differ significantly between immunohistochemical and PAM50 subtypes. We found a significant worse overall survival in Her2-enriched compared with luminal tumors. Male breast cancer seems to be mainly a genomic luminal disease with a predominance of the luminal B subtype. In addition, we found a proportion of patients with Her2-negative by immunohistochemistry but Her2-enriched profile by PAM50 tumors with a worse outcome compared with luminal subtypes that may benefit from anti-Her2 therapies.

Intrinsic subtypes and benefit from postmastectomy radiotherapy in node-positive premenopausal breast cancer patients who received adjuvant chemotherapy - results from two independent randomized trials

BACKGROUND

The study of the intrinsic molecular subtypes of breast cancer has revealed differences among them in terms of prognosis and response to chemotherapy and endocrine therapy. However, the ability of intrinsic subtypes to predict benefit from adjuvant radiotherapy has only been examined in few studies.

METHODS

Gene expression-based intrinsic subtyping was performed in 228 breast tumors collected from two independent post-mastectomy clinical trials (British Columbia and the Danish Breast Cancer Cooperative Group 82b trials), where pre-menopausal patients with node-positive disease were randomized to adjuvant radiotherapy or not. All patients received adjuvant chemotherapy and a subgroup of patients underwent ovarian ablation. Tumors were classified into intrinsic subtypes: Luminal A, Luminal B, HER2-enriched, Basal-like and Normal-like using the research-based PAM50 classifier.

RESULTS

In the British Columbia study, patients treated with radiation had an overall significant lower incidence of locoregional recurrence compared to the controls. For Luminal A tumors the risk of loco-regional recurrence was low and was further lowered by adjuvant radiation. These findings were validated in the DBCG 82b study. The individual data from the two cohorts were merged, the hazard ratio (HR) for loco-regional recurrence associated with giving radiation was 0.34 (0.19 to 0.61) overall and 0.12 (0.03 to 0.52) for Luminal A tumors.

CONCLUSIONS

In both postmastectomy trials, patients with Luminal A tumors turned out to have a significant lower incidence of loco-regional recurrence when randomized to adjuvant radiotherapy, leaving no indication to omit postmastectomy adjuvant radiation in pre-menopausal high-risk patients with Luminal A tumors. It was not possible to evaluate the effect of radiotherapy among the other subtypes because of limited sample sizes.

Optimization of RNA Extraction from Formalin-Fixed Paraffin-Embedded Blocks for Targeted Next-Generation Sequencing

Purpose

Breast cancer has a high prevalence in Korea. To achieve personalized therapy for breast cancer, long-term follow-up specimens are needed for next-generation sequencing (NGS) and multigene analysis. Formalin-fixed paraffin-embedded (FFPE) samples are easier to store than fresh frozen (FF) samples. The objective of this study was to optimize RNA extraction from FFPE blocks for NGS.

Methods

RNA quality from FF and FFPE tissues (n=5), expected RNA amount per unit area, the relationship between archiving time and quantity/quality of FFPE-extracted RNA (n=14), differences in quantitative real-time polymerase chain reaction (qRT-PCR) and NGS results, and comparisons of both techniques with tissue processing at different institutions (n=96) were determined in this study.

Results

The quality of RNA did not show any statistically significant difference between paired FF and FFPE specimens (p=0.49). Analysis of tumor cellularity gave an expected RNA amount of 33.25 ng/mm². Archiving time affected RNA quality, showing a negative correlation with RNA integrity number and a positive correlation with threshold cycle. However, RNA from samples as old as 10 years showed a 100% success rate in qRT-PCR using short primers, showing that the effect of archiving time can be overcome by proper experiment design. NGS showed a higher success rate than qRT-PCR. Specimens from institution B (n=46), which were often stored in a refrigerator for more than 6 hours and fixed without slicing, showed lower success rates and worse results than specimens from the other institutes.

Conclusion

Archived FFPE tissues can be used to extract RNA for NGS if they are properly processed before fixation. The expected amount of RNA per unit size calculated in this study will be useful for other researchers.

Predicting the Efficacy of HER2-Targeted Therapies: A Look at the Host

HER2 is overexpressed in 20% of invasive breast cancers (BCs) and correlates with a more aggressive disease. Until the advent of targeted agents, HER2 was associated with worse outcomes. Rationally designed HER2-targeted agents have been developed and introduced into clinical practice for women with HER2-amplified BC, improving disease-free and overall survival for primary and metastatic tumors. Trastuzumab, a recombinant humanized anti-HER2 monoclonal antibody, combined with chemotherapy, remains the standard of care for patients with HER2-positive BCs. However, many patients do not respond to this agent, whereas newer drugs have proven to be efficacious in clinical trials. The identification of biomarkers that select sensitive tumors and patients who will benefit from these new agents would help the incorporation of these therapies, limiting the risk of side effects and overtreatment and improving the outcomes of all patients with early-stage HER2-positive BC. We review the mechanisms of action of HER2-targeting agents, focusing on the involvement of the immune system and related predictive biomarkers.

Gene Expression Signatures and Immunohistochemical Subtypes Add Prognostic Value to Each Other in Breast Cancer Cohorts

Purpose: Gene signatures and Ki67 stratify the same breast tumor into opposing good/poor prognosis groups in approximately 20% of patients. Given this discrepancy, we hypothesized that the combination of a clinically relevant signature and IHC markers may provide more prognostic information than either classifier alone.Experimental Design: We assessed Ki67 alone or combined with ER, PR and HER2 (forming IHC subtypes), and the research versions of the Genomic Grade Index, 70-gene, cell-cycle score, recurrence score (RS), and PAM50 signatures on matching TMA/whole tumor sections and microarray data in two Swedish breast cancer cohorts of 379 and 209 patients, with median follow-up of 12.4 and 12.5 years, respectively. First, we fit Cox proportional hazards models and used the change in likelihood ratio (Δ LR) to determine the additional prognostic information provided by signatures beyond that of (i) Ki67 and (ii) IHC subtypes. Second and uniquely, we then assessed whether signatures could compete well with pathology-based IHC classifiers by calculating the additional prognostic information of Ki67/IHC subtypes beyond signatures.Results: In cohort 1, only RS and PAM50 provided additional prognostic information beyond Ki67 and IHC subtypes (Δ LR-χ2 Ki67: RS = 12.8, PAM50 = 20.7, IHC subtypes: RS = 12.9, PAM50 = 11.7). Conversely, IHC subtypes added prognostic information beyond all signatures except PAM50. Similar results were observed in cohort 2.Conclusions: RS and PAM50 provided more prognostic information than the IHC subtypes in all breast cancer patients; however, the IHC subtypes did not add any prognostic information to PAM50. Clin Cancer Res; 23(24); 7512-20. ©2017 AACR.

Gene expression information improves reliability of receptor status in breast cancer patients

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability.

We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now.

Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A ‘therapy allocation check’ identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed.

We propose an ‘expression look-up-plot’, allowing for a significant potential to improve the quality of precision medicine.

Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

HER2-positive breast cancer is lost in translation: time for patient-centered research

No biomarker beyond HER2 itself, which suffers from a low positive predictive value, has demonstrated clinical utility in breast cancer, despite numerous attempts to improve treatment tailoring for the growing number of anti-HER2 targeted therapies. This prompted us to examine the body of evidence, using a systematic approach, to identify putative predictive biomarkers in HER2-positive breast cancer, and discuss the hitherto failure to address the needs of patients. In the future, it is hoped immune-based biomarkers will predict benefit from anti-HER2 treatments in the neoadjuvant and adjuvant settings. In advanced-stage disease, the quantification of tumour heterogeneity using molecular-imaging technology has generated informative data on the success or failure of the antibody-drug conjugate T-DM1. Treatment tailoring remains a high priority, in cost-constrained health-care systems, but such tailoring will require a dramatic shift in the way translational research is being conducted, with the establishment of large, easily accessible, and well-annotated databases of candidate predictive biomarkers. Single-centre biomarker research should become a thing of the past.

Highlights of the San Antonio Breast Cancer Symposium 2016: Part 2

The 39th annual San Antonio Breast Cancer Symposium (SABCS) was convened in San Antonio, Texas, on 9-13 December 2016. More than 7000 clinicians and scientists from around the world participated in the symposium which featured a range of presentations and keynote talks pertaining to breast cancer screening, prevention, locoregional and systemic therapies. This two-part report highlights a selection of important studies presented at this premier breast cancer event with Part 1 focusing onmetastatic breast cancer, extended endocrine therapy and the prognostic significance of BRCA1/2 gene mutations. The second part of this report will discuss a range of topics including anti-HER2 directed treatments, the impact of radiotherapy on implant and autologous flap based reconstruction, biological risk predictors for ductal carcinoma-in situ (DCIS), longer term effects of dietary fat modification and the influence of aromatase inhibitors on endothelial cell function.

Pertuzumab/Trastuzumab/CT Versus Trastuzumab/CT Therapy for HER2+ Breast Cancer: Results from the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST)

BACKGROUND

Pertuzumab became a standard part of neoadjuvant therapy for human epidermal growth factor receptor 2-positive (HER2+) breast cancers approximately halfway through Neoadjuvant Breast Registry Symphony Trial (NBRST) enrollment, providing a unique opportunity to determine biologically which clinical HER2+ patients benefit most from dual targeting. As a neoadjuvant phase 4 study, NBRST classifies patients by both conventional and molecular subtyping.

METHODS

Of 308 clinical HER2+ patients enrolled in NBRST between 2011 and 2014 from 62 U.S. institutions, 297 received neoadjuvant chemotherapy (NCT) with HER2-targeted therapy and underwent surgery. This study compared the pathologic complete response (pCR) rate of BluePrint versus clinical subtypes with treatment, specifically differences between trastuzumab (T) treatment and trastuzumab and pertuzumab (T/P) treatment.

RESULTS

In this study, 60% of the patients received NCT-T, and 40% received NCT-T/P. The overall pCR rate (ypT0/isN0) was 47%. BluePrint classified 161 tumors (54%) as HER2 type, with a pCR rate of 65%. This was significantly higher than the pCR rate for the 91 HER2+ tumors (31%) classified as luminal (18%) (p = 0.00001) and the 45 tumors (15%) classified as basal (44%) (p = 0.0166). The patients treated with T/P had higher pCR rates than those treated with trastuzumab alone. The difference was most pronounced in the BluePrint luminal patients (8 vs. 31%). The highest pCR was reached by the BluePrint HER2-type patients treated with T/P (76%).

CONCLUSIONS

The addition of pertuzumab leads to increased pCR rates for all HER2+ patient groups except for the BluePrint basal-type patients. This better response was most pronounced for the BluePrint luminal-type patients.

Intrinsic Subtypes and Gene Expression Profiles in Primary and Metastatic Breast Cancer

Biological changes that occur during metastatic progression of breast cancer are still incompletely characterized. In this study, we compared intrinsic molecular subtypes and gene expression in 123 paired primary and metastatic tissues from breast cancer patients. Intrinsic subtype was identified using a PAM50 classifier and χ² tests determined the differences in variable distribution. The rate of subtype conversion was 0% in basal-like tumors, 23.1% in HER2-enriched (HER2-E) tumors, 30.0% in luminal B tumors, and 55.3% in luminal A tumors. In 40.2% of cases, luminal A tumors converted to luminal B tumors, whereas in 14.3% of cases luminal A and B tumors converted to HER2-E tumors. We identified 47 genes that were expressed differentially in metastatic versus primary disease. Metastatic tumors were enriched for proliferation-related and migration-related genes and diminished for luminal-related genes. Expression of proliferation-related genes were better at predicting overall survival in metastatic disease (OSmet) when analyzed in metastatic tissue rather than primary tissue. In contrast, a basal-like gene expression signature was better at predicting OSmet in primary disease compared with metastatic tissue. We observed correlations between time to tumor relapse and the magnitude of changes of proliferation, luminal B, or HER2-E signatures in metastatic versus primary disease. Although the intrinsic subtype was largely maintained during metastatic progression, luminal/HER2-negative tumors acquired a luminal B or HER2-E profile during metastatic progression, likely reflecting tumor evolution or acquisition of estrogen independence. Overall, our analysis revealed the value of stratifying gene expression by both cancer subtype and tissue type, providing clinicians more refined tools to evaluate prognosis and treatment. Cancer Res; 77(9); 2213-21. ©2017 AACR.

Individualized Breast Cancer Characterization through Single-Cell Analysis of Tumor and Adjacent Normal Cells

There is a need to individualize assays for tumor molecular phenotyping, given variations in the differentiation status of tumor and normal tissues in different patients. To address this, we performed single-cell genomics of breast tumors and adjacent normal cells propagated for a short duration under growth conditions that enable epithelial reprogramming. Cells analyzed were either unselected for a specific subpopulation or phenotypically defined as undifferentiated and highly clonogenic ALDH⁺/CD49f⁺/EpCAM⁺ luminal progenitors, which express both basal cell and luminal cell-enriched genes. We analyzed 420 tumor cells and 284 adjacent normal cells for expression of 93 genes that included a PAM50-intrinsic subtype classifier and stemness-related genes. ALDH⁺/CD49f⁺/EpCAM⁺ tumor and normal cells clustered differently compared with unselected tumor and normal cells. PAM50 gene-set analyses of ALDH⁺/CD49f⁺/EpCAM⁺ populations efficiently identified major and minor clones of tumor cells, with the major clone resembling clinical parameters of the tumor. Similarly, a stemness-associated gene set identified clones with divergent stemness pathway activation within the same tumor. This refined expression profiling technique distinguished genes truly deregulated in cancer from genes that identify cellular precursors of tumors. Collectively, the assays presented here enable more precise identification of cancer-deregulated genes, allow for early identification of therapeutically targetable tumor cell subpopulations, and ultimately provide a refinement of precision therapeutics for cancer treatment. Cancer Res; 77(10); 2759-69. ©2017 AACR.

Intrinsic Subtype and Therapeutic Response Among HER2-Positive Breaty st Tumors from the NCCTG (Alliance) N9831 Trial

Background

Genomic data from human epidermal growth factor receptor 2-positive (HER2+) tumors were analyzed to assess the association between intrinsic subtype and clinical outcome in a large, well-annotated patient cohort.

Methods

Samples from the NCCTG (Alliance) N9831 trial were analyzed using the Prosigna algorithm on the NanoString platform to define intrinsic subtype, risk of recurrence scores, and risk categories for 1392 HER2+ tumors. Subtypes were evaluated for recurrence-free survival (RFS) using Kaplan-Meier and Cox model analysis following adjuvant chemotherapy (n = 484) or chemotherapy plus trastuzumab (n = 908). All statistical tests were two-sided.

Results

Patients with HER2+ tumors from N9831 were primarily scored as HER2-enriched (72.1%). These individuals received statistically significant benefit from trastuzumab (hazard ratio [HR] = 0.68, 95% confidence interval [CI] = 0.52 to 0.89, P = .005), as did the patients (291 of 1392) with luminal-type tumors (HR = 0.52, 95% CI = 0.32 to 0.85, P = .01). Patients with basal-like tumors (97 of 1392) did not have statistically significantly better RFS when treated with trastuzumab and chemotherapy compared with chemotherapy alone (HR = 1.06, 95% CI = 0.53 to 2.13, P = .87).

Conclusions

The majority of clinically defined HER2-positive tumors were classified as HER2-enriched or luminal using the Prosigna algorithm. Intrinsic subtype alone cannot replace conventional histopathological evaluation of HER2 status because many tumors that are classified as luminal A or luminal B will benefit from adjuvant trastuzumab if that subtype is accompanied by HER2 overexpression. However, among tumors that overexpress HER2, we speculate that assessment of intrinsic subtype may influence treatment, particularly with respect to evaluating alternative therapeutic approaches for that subset of HER2-positive tumors of the basal-like subtype.

Whole-transcriptome analysis links trastuzumab sensitivity of breast tumors to both HER2 dependence and immune cell infiltration

While results thus far demonstrate the clinical benefit of trastuzumab, some patients do not respond to this therapy. To identify a molecular predictor of trastuzumab benefit, we conducted whole-transcriptome analysis of primary HER2+ breast carcinomas obtained from patients treated with trastuzumab-containing therapies and correlated the molecular portrait with treatment benefit.

The estimated association between gene expression and relapse-free survival allowed development of a trastuzumab risk model (TRAR), with ERBB2 and ESR1 expression as core elements, able to identify patients with high and low risk of relapse. Application of the TRAR model to 24 HER2+ core biopsies from patients treated with neo-adjuvant trastuzumab indicated that it is predictive of trastuzumab response. Examination of TRAR in available whole-transcriptome datasets indicated that this model stratifies patients according to response to trastuzumab-based neo-adjuvant treatment but not to chemotherapy alone. Pathway analysis revealed that TRAR-low tumors expressed genes of the immune response, with higher numbers of CD8-positive cells detected immunohistochemically compared to TRAR-high tumors.

The TRAR model identifies tumors that benefit from trastuzumab-based treatment as those most enriched in CD8-positive immune infiltrating cells and with high ERBB2 and low ESR1 mRNA levels, indicating the requirement for both features in achieving trastuzumab response.

CCR 20th Anniversary Commentary: Simpson's Paradox and Neoadjuvant Trials

The research article by Carey and colleagues, published in the April 15, 2007, issue of Clinical Cancer Research, described the relationship between response to neoadjuvant chemotherapy and outcome by tumor subtype. Today neoadjuvant clinical trials are often designed to provide correlative data to help identify predictive biomarkers or to focus on poor-risk patients identified by residual disease after neoadjuvant treatment.

The molecular landscape of high-risk early breast cancer: comprehensive biomarker analysis of a phase III adjuvant population

Breast cancer is a heterogeneous disease and patients are managed clinically based on ER, PR, HER2 expression, and key risk factors. We sought to characterize the molecular landscape of high-risk breast cancer patients enrolled onto an adjuvant chemotherapy study to understand how disease subsets and tumor immune status impact survival. DNA and RNA were extracted from 861 breast cancer samples from patients enrolled onto the United States Oncology trial 01062. Samples were characterized using multiplex gene expression, copy number, and qPCR mutation assays. HR⁺ patients with a PIK3CA mutant tumor had a favorable disease-free survival (DFS; HR 0.66, P=0.05), however, the prognostic effect was specific to luminal A patients (Luminal A: HR 0.67, P=0.1; Luminal B: HR 1.01, P=0.98). Molecular subtyping of triple-negative breast cancers (TNBCs) suggested that the mesenchymal subtype had the worst DFS, whereas the immunomodulatory subtype had the best DFS. Profiling of immunologic genes revealed that TNBC tumors (n=280) displaying an activated T-cell signature had a longer DFS following adjuvant chemotherapy (HR 0.59, P=0.04), while a distinct set of immune genes was associated with DFS in HR⁺ cancers. Utilizing a discovery approach, we identified genes associated with a high risk of recurrence in HR⁺ patients, which were validated in an independent data set. Molecular classification based on PAM50 and TNBC subtyping stratified clinical high-risk patients into distinct prognostic subsets. Patients with high expression of immune-related genes showed superior DFS in both HR⁺ and TNBC. These results may inform patient management and drug development in early breast cancer.

Dual Blockade of HER-2 Provides a Greater Magnitude of Benefit in Patients With Hormone-Negative Versus Hormone-Positive Breast Cancer

The dual small molecule tyrosine kinase inhibitor lapatinib blocks both human epidermal growth factor receptor (HER-1) and human epidermal growth factor receptor 2 (HER-2) tyrosine kinase activity by binding reversibly to the ATP-binding site of the receptor's intracellular domain. Lapatinib, in combination with capecitabine, has been approved in 2007 for the treatment of patients with advanced HER-2⁺ breast cancer upon progressive disease following standard chemotherapy. Approval was also extended to the treatment of postmenopausal women with advanced hormone receptor (HR)-positive and HER-2-positive breast cancer in 2010. More recently, clinical trials that have investigated the efficacy of dual HER-2 blockade in both the metastatic and neoadjuvant breast cancer settings. For example, in 2013 the European Medicines Agency approved the combination of lapatinib and trastuzumab in HER-2⁺/HR^- patients. We review the efficacy results from dual HER-2 blockade studies and present new post hoc analysis efficacy data according to HR status. We show that dual blockade of HER-2 appears to provide a greater magnitude of benefit in the HR^- versus the HR⁺ subgroup of patients. Finally, we examine the potential of molecularly subtyping HER-2⁺ tumors using the PAM50 test as a predictor of response to treatment with the combination of trastuzumab and lapatinib.

Predictive biomarkers in the treatment of HER2-positive breast cancer: an ongoing challenge

The transmembrane tyrosine kinase receptor HER2 is overexpressed in 20% of invasive breast cancers and is associated with more aggressive disease. Until the advent of targeted agents, HER2 was associated with worse outcome. Trastuzumab, a recombinant humanized anti-HER2 monoclonal antibody, combined with chemotherapy improves disease-free and overall survival in both primary and metastatic tumors and represents a foundation of care for patients with HER2-positive breast cancers. However, a sizeable number of patients do not respond to this reagent, indicating the need for a biomarker able to recognize resistant tumors. Here, we review various studies on mechanisms of action and resistance to trastuzumab that have proven relevant in understanding how tumor care can be tailored to all HER2-positive patients.

Signatures of breast cancer metastasis at a glance

Gene expression profiling has yielded expression signatures from which prognostic tests can be derived to facilitate clinical decision making in breast cancer patients. Some of these signatures are based on profiling of whole tumor tissue (tissue signatures), which includes all tumor and stromal cells. Prognostic markers have also been derived from the profiling of metastasizing tumor cells, including circulating tumor cells (CTCs) and migratory-disseminating tumor cells within the primary tumor. The metastasis signatures based on CTCs and migratory-disseminating tumor cells have greater potential for unraveling cell biology insights and mechanistic underpinnings of tumor cell dissemination and metastasis. Of clinical interest is the promise that stratification of patients into high or low metastatic risk, as well as assessing the need for cytotoxic therapy, might be improved if prognostics derived from these two types of signatures are used in a combined way. The aim of this Cell Science at a Glance article and accompanying poster is to navigate through both types of signatures and their derived prognostics, as well as to highlight biological insights and clinical applications that could be derived from them, especially when they are used in combination.

Neoadjuvant therapy for early-stage breast cancer: the clinical utility of pertuzumab

Approximately 20% of breast cancer patients harbor tumors that overexpress human epidermal growth factor receptor 2 (HER2; also known as ErbB2), a receptor tyrosine kinase that belongs to the epidermal growth factor receptor family of receptor tyrosine kinases. HER2 amplification and hyperactivation drive the growth and survival of breast cancers through the aberrant activation of proto-oncogenic signaling systems, particularly the Ras/MAP kinase and PI3K/AKT pathways. Although HER2-positive (HER2(+)) breast cancer was originally considered to be a highly aggressive form of the disease, the clinical landscape of HER2(+) breast cancers has literally been transformed by the approval of anti-HER2 agents for adjuvant and neoadjuvant settings. Indeed, pertuzumab is a novel monoclonal antibody that functions as an anti-HER2 agent by targeting the extracellular dimerization domain of the HER2 receptor; it is also the first drug to receive an accelerated approval by the US Food and Drug Administration for use in neoadjuvant settings in early-stage HER2(+) breast cancer. Here, we review the molecular and cellular factors that contribute to the pathophysiology of HER2 in breast cancer, as well as summarize the landmark preclinical and clinical findings underlying the approval and use of pertuzumab in the neoadjuvant setting. Finally, the molecular mechanisms operant in mediating resistance to anti-HER2 agents, and perhaps to pertuzumab as well, will be discussed, as will the anticipated clinical impact and future directions of pertuzumab in breast cancer patients.

Molecular Testing and the Pathologist's Role in Clinical Trials of Breast Cancer

Molecular characterization of breast cancer is pivotal for identifying new molecular targets and determining the appropriate treatment choices. Advances in molecular profiling technology have given greater insight into this heterogeneous disease, over and above hormone receptor and human epidermal growth factor receptor 2 status. Agents targeting recently characterized molecular biomarkers are under clinical development; the success of these targeted agents is likely to depend on identifying the patient population most likely to benefit. Therefore, clinical trials of breast cancer often require prescreening for, or stratification by, relevant molecular markers or exploratory analyses of biomarkers that can predict or monitor the response to treatment. Consequently, the role of the pathologist has become increasingly important. The key considerations for pathologists include tissue availability, ownership of archival tissue, type of diagnostic/biomarker test required, method of sample processing, concordance between different tests and testing centers, and tumor heterogeneity. In the present review, we explore how pathology is used in current clinical trials of breast cancer and describe the various technologies available for molecular testing. Furthermore, the factors required for the successful application of pathology in clinical trials of breast cancer and the issues that can arise and how these can be circumvented are discussed.

Study design requirements for RNA sequencing-based breast cancer diagnostics

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Response and survival of breast cancer intrinsic subtypes following multi-agent neoadjuvant chemotherapy

BACKGROUND

Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC).

METHODS

Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used.

RESULTS

Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7%, 30.6%, 18.2%, and 10.3% of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35% across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5% (92.8-100.0%) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4% of Luminal A tumors with clinically node-negative disease).

CONCLUSIONS

Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any).

High HER2/Centromeric Probe for Chromosome 17 Fluorescence In Situ Hybridization Ratio Predicts Pathologic Complete Response and Survival Outcome in Patients Receiving Neoadjuvant Systemic Therapy With Trastuzumab for HER2-Overexpressing Locally Advanced Breast Cancer

BACKGROUND

The present study was performed to determine whether the human epidermal growth factor receptor-related 2 (HER2)/centromeric probe for chromosome 17 fluorescence in situ hybridization (FISH) ratio is a predictor of a pathologic complete response (pCR), recurrence-free survival (RFS), and/or overall survival (OS) in patients receiving neoadjuvant systemic treatment (NST) with trastuzumab (NST-T) for HER2+ locally advanced breast cancer (LABC).

PATIENTS AND METHODS

The present retrospective study included 555 patients with HER2+ LABC who had undergone NST and definitive surgery (1999-2012); 373 had concurrently received trastuzumab. HER2-positivity was considered present with an immunohistochemical score of 3+ and/or HER2 FISH ratio of ≥2.0. We used logistic regression analysis and Cox proportional hazard modeling to determine whether a high HER2 FISH ratio, either as a continuous variable or with a cutoff of ≥7.0, would predict for pCR (no invasive disease in the breast and no tumor in the ipsilateral axillary lymph nodes), RFS, and/or OS.

RESULTS

The pCR group's median HER2 FISH ratio was significantly higher than that of the non-pCR group (6.4 vs. 5.2; p = .003). The logistic regression model demonstrated that the independent predictors of pCR included a high HER2 FISH ratio as a continuous variable (p = .04). The multicovariate Cox proportional hazard model showed that a high HER2 FISH ratio (with a cutoff of ≥7.0 or as a continuous variable) was a significant prognostic indicator of longer RFS time (p = .047 and p = .04, respectively). Similarly, a high HER2 FISH ratio of ≥7.0 was associated with longer OS (p = .06).

CONCLUSION

A high HER2 FISH ratio is a predictor of pCR in patients with HER2+ LABC who receive NST-T.

IMPLICATIONS FOR PRACTICE

This study demonstrated the optimal predictive and prognostic value of a HER2/centromeric probe for chromosome 17 FISH ratio for primary HER2+ breast cancer treated with trastuzumab combined with neoadjuvant systemic treatment (NST-T). This suggests that a high HER2 FISH ratio is a potential indicator for a high pathologic complete response rate and a better prognosis when patients are treated with NST-T.

Hormone receptor status predicts the clinical outcome of human epidermal growth factor 2-positive metastatic breast cancer patients receiving trastuzumab therapy: a multicenter retrospective study

Objectives

Trastuzumab, a humanized monoclonal antibody that binds human epidermal growth factor receptor 2 (HER2), dramatically improves the clinical outcomes of HER2-positive breast cancer. Emerging evidence implied that the clinical behavior and sensitivity to targeted agents in HER2-positive breast cancer differed by hormone receptor (HR) status. The objective of this study was to determine the effect of the HR status on survival benefit of HER2-positive metastatic breast cancer when treated with anti-HER2-targeted therapy in People’s Republic of China.

Methods

Metastatic breast cancer patients with HER2-positive diseases across six cancer centers in People’s Republic of China were retrospectively analyzed in our study. Patients were classified into four groups according to HR/HER2 status and trastuzumab treatment: HER2+/HR+ patients with first-line trastuzumab treatment, HER2+/HR+ patients with no trastuzumab treatment, HER2+/HR− patients with first-line trastuzumab treatment, and HER2+/HR− patients with no trastuzumab treatment. Kaplan–Meier analysis, log-rank test, and multivariate analysis were performed during analysis.

Results

A total of 295 patients were included in the final analysis. The median overall survival was 30 months (95% confidence interval: 27.521–32.479). Among patients with HER2+/HR− disease, significant survival benefit was observed when treated with trastuzumab (30 vs 21 months, P=0.000). However, in patients with HER2+/HR+ disease, trastuzumab administration had a survival improvement trend but no significant statistical differences (36 vs 30 months, P=0.258). In the multivariate analysis, HR status was an independent predictor of overall survival and trastuzumab treatment had significantly decreased risk of death in HER2+/HR− patients (hazard ratio =0.330).

Conclusion

HR status is an independent predictor of overall survival in HER2-positive metastatic breast cancer patients and patients with HER2+/HR− subtype might be associated with more survival benefits when treated with trastuzumab-based regimens.

Competitive Binding Between Id1 and E2F1 to Cdc20 Regulates E2F1 Degradation and Thymidylate Synthase Expression to Promote Esophageal Cancer Chemoresistance

PURPOSE

Chemoresistance is a major obstacle in cancer therapy. We found that fluorouracil (5-FU)-resistant esophageal squamous cell carcinoma cell lines, established through exposure to increasing concentrations of 5-FU, showed upregulation of Id1, IGF2, and E2F1. We hypothesized that these genes may play an important role in cancer chemoresistance.

EXPERIMENTAL DESIGN

In vitro and in vivo functional assays were performed to study the effects of Id1-E2F1-IGF2 signaling in chemoresistance. Quantitative real-time PCR, Western blotting, immunoprecipitation, chromatin immunoprecipitation, and dual-luciferase reporter assays were used to investigate the molecular mechanisms by which Id1 regulates E2F1 and by which E2F1 regulates IGF2. Clinical specimens, tumor tissue microarray, and Gene Expression Omnibus datasets were used to analyze the correlations between gene expressions and the relationships between expression profiles and patient survival outcomes.

RESULTS

Id1 conferred 5-FU chemoresistance through E2F1-dependent induction of thymidylate synthase expression in esophageal cancer cells and tumor xenografts. Mechanistically, Id1 protects E2F1 protein from degradation and increases its expression by binding competitively to Cdc20, whereas E2F1 mediates Id1-induced upregulation of IGF2 by binding directly to the IGF2 promoter and activating its transcription. The expression level of E2F1 was positively correlated with that of Id1 and IGF2 in human cancers. More importantly, concurrent high expression of Id1 and IGF2 was associated with unfavorable patient survival in multiple cancer types.

CONCLUSIONS

Our findings define an intricate E2F1-dependent mechanism by which Id1 increases thymidylate synthase and IGF2 expressions to promote cancer chemoresistance. The Id1-E2F1-IGF2 regulatory axis has important implications for cancer prognosis and treatment.

Subtype-Specific Metagene-Based Prediction of Outcome after Neoadjuvant and Adjuvant Treatment in Breast Cancer

PURPOSE

In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster-based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients.

EXPERIMENTAL DESIGN

A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER(+)HER2(-), the proliferation and ER-related metagenes were combined to define three risk groups. In HER2(+) and ER(-)HER2(-) risk groups were defined by tertiles of an immune-related metagene.

RESULTS

The high-proliferation/low-ER group of ER(+)HER2(-) breast cancer had significantly higher pCR rate [OR, 5.01 (1.76-17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63-8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER(-)HER2(-) and HER2(+) breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79-8.95); P = 0.0009]. In ER(-)HER2(-), after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2(+) breast cancer treated with chemotherapy the association with risk of relapse was not significant.

CONCLUSIONS

We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents.

Neoadjuvant treatment of breast cancer: maximizing pathologic complete response rates to improve prognosis

PURPOSE OF REVIEW

Neoadjuvant therapy is very often an adequate alternative to adjuvant therapy. This review summarizes the recent advances made in the area of neoadjuvant therapy in breast cancer. The focus will lie on recently published clinical trials, but will not further highlight surgical, imaging and radio-oncological issues related to neoadjuvant therapy.

RECENT FINDINGS

Within the past year, it has been discussed if neoadjuvant treatment can be used as a faster way to get access to new therapies, based on new data in HER2+ breast cancer, suggesting a higher pathological complete response rate when a dual anti-HER2 therapy was used. Nevertheless, this higher pathological complete response rate does not necessarily always translate into a better survival. In triple negative breast cancer, carboplatin could be identified as an asset for patients, especially in patients with gBRCA mutations. However, mature long-term data are still missing. The neoadjuvant approach is ideal to identify new biomarkers which predict response or resistance to the given treatment. Tumour-infiltrating lymphocytes and PIK3CA mutations are amongst the most promising markers.

SUMMARY

Neoadjuvant treatment should be considered for all patients with HER2-positive or triple negative breast cancer. Clinical trials in this setting are currently investigating new approaches.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay

BACKGROUND

The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.

METHODS

514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.

RESULTS

The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.

CONCLUSIONS

The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Tumor-Derived Cell Lines as Molecular Models of Cancer Pharmacogenomics

Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic alterations. Often, these changes underlie cancer development, progression, and drug resistance, so the utility of model systems rests on their ability to recapitulate the genomic aberrations observed in primary tumors. Tumor-derived cell lines have long been used to study the underlying biologic processes in cancer, as well as screening platforms for discovering and evaluating the efficacy of anticancer therapeutics. Multiple -omic measurements across more than a thousand cancer cell lines have been produced following advances in high-throughput technologies and multigroup collaborative projects. These data complement the large, international cancer genomic sequencing efforts to characterize patient tumors, such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Given the scope and scale of data that have been generated, researchers are now in a position to evaluate the similarities and differences that exist in genomic features between cell lines and patient samples. As pharmacogenomics models, cell lines offer the advantages of being easily grown, relatively inexpensive, and amenable to high-throughput testing of therapeutic agents. Data generated from cell lines can then be used to link cellular drug response to genomic features, where the ultimate goal is to build predictive signatures of patient outcome. This review highlights the recent work that has compared -omic profiles of cell lines with primary tumors, and discusses the advantages and disadvantages of cancer cell lines as pharmacogenomic models of anticancer therapies.

Clinical implications of the intrinsic molecular subtypes of breast cancer

Gene-expression profiling has had a considerable impact on our understanding of breast cancer biology. During the last 15 years, 5 intrinsic molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched, Basal-like and Claudin-low) have been identified and intensively studied. In this review, we will focus on the current and future clinical implications of the intrinsic molecular subtypes beyond the current pathological-based classification endorsed by the 2013 St. Gallen Consensus Recommendations. Within hormone receptor-positive and HER2-negative early breast cancer, the Luminal A and B subtypes predict 10-year outcome regardless of systemic treatment administered as well as residual risk of distant recurrence after 5 years of endocrine therapy. Within clinically HER2-positive disease, the 4 main intrinsic subtypes can be identified and dominate the biological and clinical phenotype. From a clinical perspective, patients with HER2+/HER2-enriched disease seem to benefit the most from neoadjuvant trastuzumab, or dual HER2 blockade with trastuzumab/lapatinib, in combination with chemotherapy, and patients with HER2+/Luminal A disease seem to have a relative better outcome compared to the other subtypes. Finally, within triple-negative breast cancer (TNBC), the Basal-like disease predominates (70-80%) and, from a biological perspective, should be considered a cancer-type by itself. Importantly, the distinction between Basal-like versus non-Basal-like within TNBC might predict survival following (neo)adjvuvant multi-agent chemotherapy, bevacizumab benefit in the neoadjuvant setting (CALGB40603), and docetaxel vs. carboplatin benefit in first-line metastatic disease (TNT study). Overall, this data suggests that intrinsic molecular profiling provides clinically relevant information beyond current pathology-based classifications.

Tailoring therapies--improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015

The 14th St Gallen International Breast Cancer Conference (2015) reviewed substantial new evidence on locoregional and systemic therapies for early breast cancer. Further experience has supported the adequacy of tumor margins defined as 'no ink on invasive tumor or DCIS' and the safety of omitting axillary dissection in specific cohorts. Radiotherapy trials support irradiation of regional nodes in node-positive disease. Considering subdivisions within luminal disease, the Panel was more concerned with indications for the use of specific therapies, rather than surrogate identification of intrinsic subtypes as measured by multiparameter molecular tests. For the treatment of HER2-positive disease in patients with node-negative cancers up to 1 cm, the Panel endorsed a simplified regimen comprising paclitaxel and trastuzumab without anthracycline as adjuvant therapy. For premenopausal patients with endocrine responsive disease, the Panel endorsed the role of ovarian function suppression with either tamoxifen or exemestane for patients at higher risk. The Panel noted the value of an LHRH agonist given during chemotherapy for premenopausal women with ER-negative disease in protecting against premature ovarian failure and preserving fertility. The Panel noted increasing evidence for the prognostic value of commonly used multiparameter molecular markers, some of which also carried prognostic information for late relapse. The Panel noted that the results of such tests, where available, were frequently used to assist decisions about the inclusion of cytotoxic chemotherapy in the treatment of patients with luminal disease, but noted that threshold values had not been established for this purpose for any of these tests. Multiparameter molecular assays are expensive and therefore unavailable in much of the world. The majority of new breast cancer cases and breast cancer deaths now occur in less developed regions of the world. In these areas, less expensive pathology tests may provide valuable information. The Panel recommendations on treatment are not intended to apply to all patients, but rather to establish norms appropriate for the majority. Again, economic considerations may require that less expensive and only marginally less effective therapies may be necessary in less resourced areas. Panel recommendations do not imply unanimous agreement among Panel members. Indeed, very few of the 200 questions received 100% agreement from the Panel. In the text below, wording is intended to convey the strength of Panel support for each recommendation, while details of Panel voting on each question are available in supplementary Appendix S2, available at Annals of Oncology online.