RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early invasive breast cancer. Based on RNA-sequencing we aimed to develop single-sample predictor (SSP) models for conventional clinical markers, molecular intrinsic subtype and risk of recurrence (ROR).MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set and a reserved test set. We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna® in two external cohorts. Prognostic value was assessed using distant recurrence-free interval.ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC was assessed as equivalent. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade, respectively. SSP concordance with Prosigna® was high for subtype and moderate and high for ROR risk category. In pooled analysis, concordance between SSP and Prosigna® for emulated treatment recommendation for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of chemotherapy.ConclusionsSSP models for histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in postmenopausal ER+/HER2-/N0 patients suggested that molecular testing could lead to a changed therapy recommendation for almost one-fifth of patients

Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others

Background: Previous reports identifying discordance between multiparameter tests at the individual patient level have been largely attributed to methodological shortcomings of multiple in silico studies. Comparisons between tests, when performed using actual diagnostic assays, have been predicted to demonstrate high degrees of concordance. OPTIMA prelim compared predicted risk stratification and subtype classification of different multiparameter tests performed directly on the same population. Methods: Three hundred thirteen women with early breast cancer were randomized to standard (chemotherapy and endocrine therapy) or test-directed (chemotherapy if Oncotype DX recurrence score >25) treatment. Risk stratification was also determined with Prosigna (PAM50), MammaPrint, MammaTyper, NexCourse Breast (IHC4-AQUA), and conventional IHC4 (IHC4). Subtype classification was provided by Blueprint, MammaTyper, and Prosigna. Results: Oncotype DX predicted a higher proportion of tumors as low risk (82.1%, 95% confidence interval [CI] = 77.8% to 86.4%) than were predicted low/intermediate risk using Prosigna (65.5%, 95% CI = 60.1% to 70.9%), IHC4 (72.0%, 95% CI = 66.5% to 77.5%), MammaPrint (61.4%, 95% CI = 55.9% to 66.9%), or NexCourse Breast (61.6%, 95% CI = 55.8% to 67.4%). Strikingly, the five tests showed only modest agreement when dichotomizing results between high vs low/intermediate risk. Only 119 (39.4%) tumors were classified uniformly as either low/intermediate risk or high risk, and 183 (60.6%) were assigned to different risk categories by different tests, although 94 (31.1%) showed agreement between four of five tests. All three subtype tests assigned 59.5% to 62.4% of tumors to luminal A subtype, but only 121 (40.1%) were classified as luminal A by all three tests and only 58 (19.2%) were uniformly assigned as nonluminal A. Discordant subtyping was observed in 123 (40.7%) tumors. Conclusions: Existing evidence on the comparative prognostic information provided by different tests suggests that current multiparameter tests provide broadly equivalent risk information for the population of women with estrogen receptor (ER)–positive breast cancers. However, for the individual patient, tests may provide differing risk categorization and subtype information

Limitations in predicting PAM50 intrinsic subtype and risk of relapse score with Ki67 in estrogen receptor-positive HER2-negative breast cancer

PAM50/Prosigna gene expression-based assay identifies three categorical risk of relapse groups (ROR-low, ROR-intermediate and ROR-high) in post-menopausal patients with estrogen receptor estrogen receptor-positive (ER+)/ HER2-negative (HER2-) early breast cancer. Low risk patients might not need adjuvant chemotherapy since their risk of distant relapse at 10-years is below 10% with endocrine therapy only. In this study, 517 consecutive patients with ER+/HER2- and node-negative disease were evaluated for Ki67 and Prosigna. Most of Luminal A tumors (65.6%) and ROR-low tumors (70.9%) had low Ki67 values (0-10%); however, the percentage of patients with ROR-medium or ROR-high disease within the Ki67 0-10% group was 42.7% (with tumor sizes ≤2 cm) and 33.9% (with tumor sizes > 2 cm). Finally, we found that the optimal Ki67 cutoff for identifying Luminal A or ROR-low tumors was 14%. Ki67 as a surrogate biomarker in identifying Prosigna low-risk outcome patients or Luminal A disease in the clinical setting is unreliable. In the absence of a well-validated prognostic gene expression-based assay, the optimal Ki67 cutoff for identifying low-risk outcome patients or Luminal A disease remains at 14%

Advantages and limitations of molecular genetic prognostic tests for breast cancer. A systematic literature review

Background: Breast cancer is the most commonly diagnosed cancer in women internationally, and the most common cause of cancer related death among women. There are many ways to classify breast cancer, and breast cancer can be divided into several subgroups depending on which classification system is used. Pathological reports of breast carcinoma not only depend on one of these systems but include histopathological classification, grade of the tumor, and immunohistochemical (IHC) parameters like estrogen receptor (ER), progesterone receptor (PR), HER2- and Ki67-status. With the development of microarrays, it is now possible to analyze the genes of the cells, and with gene expression profiling (GEP) we have been able to evaluate breast cancer prognosis based on the gene expression of the cancer cells. Different genetic signatures of breast cancer have been obtained through DNA microarray technology, RNA sequencing and bioinformatic models. Some of these signatures have been validated through clinical studies and been translated into commercial prognostic assays. Four such commercial prognostic assays are Oncotype DX, MammaPrint, EndoPredict and PAM5-ROR. Methods: A literature search were conducted on the databases Medline and Embase. The inclusion criteria of the search were based on the Population, Intervention, Comparison and Outcome (PICO) framework. The search included terms to identify studies assessing the prognostic or economic aspects of Oncotype DX, MammaPrint, EndoPredict or Prosigna. Out of a total of 290 identified studies, 5 were included in this thesis. Results: Through the systematic literature search only studies focusing on Oncotype DX were included. The litterateur search disclosed that the Oncotype DX recurrence score (RS) is significantly associated with worse prognosis. The Oncotype DX RS were associated with both overall survival, disease free survival and local recurrence. The literature search also disclosed that Oncotype DX may be cost effective, especially in the high-risk RS group, were chemotherapy seemed to be clearly cost-effective because of the gain of additional quality- adjusted life-years (QUALY) at a low cost. Conclusion: The findings of this thesis suggest that Oncotype DX have an independent prognostic significance and is significantly associated with survival and risk of recurrence and may be helpful to guide treatment. Studies also show that Oncotype DX may be a cost effective alternative when used to guide adjuvant chemotherapy treatment

Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®.

Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (rc(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and rc(ROR) = 0.97 (95% CI 0.94-0.98) with LoA of -8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data

Risk stratification in early breast cancer in premenopausal and postmenopausal women: integrating genomic assays with clinicopathological features.

PURPOSE OF REVIEW: There is growing consensus that genomic assays provide useful complementary information to clinicopathological features in oestrogen receptor-positive breast cancers. Here, ongoing research with multigene tests used for postmenopausal breast cancer and new emerging prognostic and predictive markers for pre and postmenopausal women are summarised. RECENT FINDINGS: Results of the TAILORx trial have shown that women with an intermediate risk score do not benefit from adjuvant chemotherapy. Prosgina has been further investigated in a contemporary patient population in postmenopausal women and its use has been extended for premenopausal women. The EndoPredict was extensively used in decision-impact studies showing that its use can potentially reduce the need for adjuvant chemotherapy. Several new genomic assays have been developed, with some of them showing promising use for women with early oestrogen receptor-positive breast cancer. SUMMARY: New areas of research for prediction of recurrence and risk stratification involve the development of immune gene signatures that carry modest but significant prognostic value. The recent expansion of high-throughput technology platforms including circulating tumour DNA/RNA and microRNA offer new opportunities to improve prediction models, particularly in women with oestrogen receptor-negative disease and premenopausal women. Genomic assays have clearly improved prognostication of early oestrogen receptor-positive breast cancer but it is clear that standard clinicopathological parameters are still very important when identifying patient for adjuvant chemotherapy.is work has been supported by Cancer Research U

Extended Adjuvant Endocrine Treatment in Luminal Breast Cancers in the Era of Genomic Tests

In patients with early-stage endocrine receptor-positive (ER+) breast cancer (BC), adjuvant endocrine therapy (ET) for 5 years is the standard of care. However, for some patients, the risk of recurrence remain high for up to 15 years after diagnosis and extended ET beyond 5 years may be a reasonable option. Nevertheless, this strategy significantly increases the occurrence of side effects. Here we summarize the available evidence from randomized clinical trials on the efficacy and safety profile of extended ET and discuss available clinical and genomic tools helpful to select eligible patients in daily clinical practice