The Prosigna gene expression assay and responsiveness to adjuvant cyclophosphamide-based chemotherapy in premenopausal high-risk patients with breast cancer

Hormone receptor-positive early breast cancer in young women: A comprehensive review

The incidence of breast cancer in ≤ 40 yr-old women (YWBC) has been steadily increasing in recent decades. Although this group of patients represents less than 10 % of all newly diagnosed BC cases it encompasses a significant burden of disease. Usually underrepresented in clinical trials, YWBCs are also characterized by late diagnoses and poorly differentiated, aggressive-subtype disease, partly explaining its poor prognosis along with a high recurrence risk, and high mortality rates. On the other hand, YWBC treatment poses unique challenges such as preservation of fertility, and long-term toxicity and adverse events. Herein, we summarize the current evidence in hormone receptor-positive YWBC including specific risk factors, clinicopathologic and genomic features, and available evidence on response to chemotherapy and endocrine therapy. Overall, we advocate for a more comprehensive multidisciplinary healthcare model to improve the outcomes and the quality of life of this subset of younger patients.

Age-Related Clusters and Favorable Immune Phenotypes in Young Breast Cancer Patients

Breast cancer (BC) patients aged <40 years at diagnosis experience aggressive disease and poorer survival compared with women diagnosed with BC at 40 to 49 years, but the age-related biology is described to little extent. Here, we explored transcriptional alterations in BC to gain better understanding of age-related tumor biology. We studied a subset of the Bergen in-house cohort (n = 127; age range, 26-49 years) and used the NanoString Breast Cancer 360 expression panel on formalin-fixed paraffin-embedded BC tissue, and publicly available global BC messenger RNA expression data (n = 204; age range, 22-49 years), to explore differentially expressed genes between the young (age <40 years) and older (age 40-49 years) patients. Unsupervised hierarchical clustering was applied to identify gene expression-based patient clusters. We applied established computational approaches to define the PAM50 subtypes, risk of recurrence scores (ROR), and risk groups and to infer the proportions of 22 immune cell types from bulk gene expression profiles of patients aged <50 years at BC diagnosis. Differentially expressed genes and gene sets were investigated using OncoEnrichR and g:Profiler to describe functional profiles and pathway enrichment. We identified 4 age-related patient clusters presenting distinct characteristics of PAM50 subtypes and ROR profiles, which demonstrated independent prognostic value when adjusted for traditional clinicopathologic variables and the known molecular subtypes. Our findings showed better survival than expected in the basal-enriched cluster 2 and in triple-negative and basal-like BC. Deconvolution analyses of immunophenotypes indicated higher levels of M0 and M1 macrophages than M2 macrophages in subsets of young BC. Our approach identifies age-based patient clusters with distinct clinicopathologic profiles, to a large extent overlapping with the PAM50 subtypes, although with independent prognostic values in multivariate survival analyses. The patient clusters provided new insight in the immune cell distribution across tumor subtypes, potentially contributing to survival differences between the clusters and the molecular subtypes and indicating age-related mechanisms improving outcome. Our study confirms the applicability of ROR as a valid prognosticator also in a young BC cohort.

Selecting postoperative adjuvant systemic therapy for early-stage breast cancer: An updated assessment and systematic review of leading commercially available gene expression assays

Gene expression assays (GEAs) can guide treatment for early-stage breast cancer. Several large prospective randomized clinical trials, and numerous additional studies, now provide new information for selecting an appropriate GEA. This systematic review builds upon prior reviews, with a focus on five widely commercialized GEAs (Breast Cancer Index®, EndoPredict®, MammaPrint®, Oncotype DX®, and Prosigna®). The comprehensive dataset available provides a contemporary opportunity to assess each GEA's utility as a prognosticator and/or predictor of adjuvant therapy benefit.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

Use of the Gene Expression Test Prosigna® in Premenopausal Patients with HR+, HER2- Early Breast Cancer: Correlation of the Results with the Proliferation Marker Ki-67

Introduction

In hormone receptor-positive (ER+/PR+) and human epidermal growth factor receptor 2-negative (HER2-) early-stage breast cancer (EBC), gene expression tests such as the Prosigna are increasingly used since classic clinicopathological parameters and the proliferation factor Ki-67 often do not allow a definite therapy decision regarding an adjuvant chemotherapy. While the Prosigna test has been validated for postmenopausal patients, few data are available regarding its use in premenopausal patients. The present study compared the Prosigna test with the Ki-67 index in premenopausal patients.

Materials and Methods

Premenopausal patients with HR+ HER2-, pN0-1, G1-2 EBC were retrospectively enrolled (n = 55). The Prosigna assay was performed in formalin-fixed paraffin-embedded tumor samples of surgical resection specimens. Ki-67 was reassessed in original diagnostic core needle biopsy specimens and defined as low, intermediate, or high with the threshold of <10%, 10-24%, ≥25%.

Results

According to Ki-67, patients were in the low (LR)-, intermediate (IR)-, and high-risk (HR) groups in 40%, 36%, and 24% of the cases. The Prosigna gene signature assay assessed the risk of recurrence as LR for 45% of the patients, IR for 35%, and HR for 20%. The most frequent intrinsic subtypes were luminal A in 73% and luminal B in 24% of the patients. A moderate correlation was found between Prosigna and Ki-67 scores with a Pearson correlation coefficient of 0.51. In the overall cohort, 47% of the Ki-67-based therapy decision would correspond to those based on the Prosigna score. After exclusion of IR patients, matching of low/low or high/high results was observed in 57% of the cases.

Conclusion

According to the present study, there is only limited concordance regarding the risk group stratification between Ki-67 and Prosigna-based risk assessment. The relevance and frequency of premenopausal breast cancer emphasizes the need for further evaluation of gene expression analyses in this setting and the correlation with classic clinicopathological parameters regarding therapy decision-making.

Analysis of the association of HER-2 low carcinomas and PAM50 assay in hormone receptor positive early-stage breast cancer

BACKGROUND

HER2-low has emerged as a new predictive biomarker in metastatic breast cancer. However, its prognostic value in early-stage carcinomas needs to be revisited. We aimed to evaluate the association of HER2-low carcinomas with PAM50 risk groups combined with clinicopathological variables in early breast cancer.

METHODS

We conducted a retrospective analysis of 332 patients with early-stage breast cancer that underwent PAM50 signature analysis between 2015 and 2021at Hospital Universitario 12 de Octubre (Madrid, Spain). Clinical and pathological variables were collected from medical records. After adjusting for potential confounders, we estimated Odds Ratio (OR) and 95% confidence interval for high-risk PAM50 subgroup, comparing HER2-low versus HER2-zero carcinomas by multivariable logistic regression. P values below 0.05 were deemed statistically significant.

RESULTS

192 (57%) patients were classified as HER2-low carcinomas. Median follow-up was 34 months. Adjusted OR for high-risk PAM50 when comparing HER2-low versus HER2-zero carcinomas was 1.31 (95% CI: 0.75-2.30, p = 0.33). The multivariable model detected significant associations for Ki-67% (≥20% vs. <20%: OR = 4.03, 95% CI: 2.15-7.56, p < 0.001), T staging category (T2/T3 vs. T1: OR = 3.44, 95% CI: 1.96-6.04, p < 0.001), progesterone receptor (PR ≥ 20% vs. <20%: OR = 0.44, 95% CI: 0.23-0.83, p = 0.01), nodal staging category (N+ vs. N0: OR = 3.8, 95% CI: 1.89-7.62, p < 0.001) and histological grade (grade 2 vs. 1: OR = 2.41, 95% CI: 1.01-5.73, p = 0.04; grade 3 vs 1: OR = 5.40, 95%CI: 1.98-14.60, p = 0.001).

CONCLUSIONS

In this early-stage breast cancer cohort, HER2-low was not associated with a high-risk PAM50 compared to HER2-zero carcinomas. Ki-67 ≥ 20%, T2/T3, histological grade 2/3, N+ and PR<20% were significantly associated to a high-risk PAM50.

Hormone Receptor-Positive / HER2-Negative Early Breast Cancer High-Risk Population: An Algorithm for Optimization Systemic Adjuvant Treatment Based on 2022 Updates

Prognostic and predictive factors for early and late distant distance recurrence risk in estrogen-receptor positive and HER2-receptor negative early breast cancer are well known, but not all these variables work equally for the prediction. The following are the most widely accepted variables for categorizing risk levels: clinic-pathologic features (tumor size, lymph node involvement, histological grade, age, menopausal status, Ki-67 expression, estrogen, and progesterone expression), primary systemic treatment response (pathologic response and/or Ki-67 downstaging), and gene expression signatures stratification. Treatment guidelines from cancer societies and collaborative groups, online predict-tools, real-world data and experts' opinion recommends different adjuvant strategies (chemotherapy, endocrine therapy, ovarian suppression, olaparib, or abemaciclib) depending on the low (< 10%), intermediate (10%-20%) or high-risk of distance recurrence at least in the first 5 years. Multiple randomized prospective trials were updated in 2022, that evidence allow us to perform a stratification of risk in pre- and postmenopausal women with estrogen-receptor positive and HER2-receptor negative early breast cancer based on a combination of clinic-pathologic features and genomic assays and guide the adjuvant systemic treatment recommendation for those with high risk.

Prognostic value of HER2-low status in breast cancer: a systematic review and meta-analysis

BACKGROUND

Human epidermal growth factor receptor 2 (HER2)-low expression in breast cancer has been recently identified as a new therapeutic target. However, it is unclear if HER2-low status has an independent impact on prognosis.

MATERIALS AND METHODS

A systematic literature research was carried out to identify studies comparing survival outcomes of patients affected by HER2-low versus HER2-zero breast cancer. Using random-effects models, pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for progression-free survival (PFS) and overall survival (OS) in the metastatic setting as well as disease-free survival (DFS), OS and pathological complete response (pCR) in the early setting. Subgroup analyses by hormone receptor (HoR) status were carried out. The study protocol is registered on PROSPERO (n.CRD42023390777).

RESULTS

Among 1916 identified records, 42 studies including 1 797 175 patients were eligible. In the early setting, HER2-low status was associated with significant improved DFS (HR 0.86, 95% CI 0.79-0.92, P < 0.001) and OS (HR 0.90, 95% CI 0.85-0.95, P < 0.001) when compared to HER2-zero status. Improved OS was observed for both HoR-positive and HoR-negative HER2-low populations, while DFS improvement was observed only in the HoR-positive subgroup. HER2-low status was significantly associated with a lower rate of pCR as compared to HER2-zero status both in the overall population (OR 0.74, 95% CI 0.62-0.88, P = 0.001) and in the HoR-positive subgroup (OR 0.77, 95% CI 0.65-0.90, P = 0.001). In the metastatic setting, patients with HER2-low breast cancers showed better OS when compared with those with HER2-zero tumours in the overall population (HR 0.94, 95% CI 0.89-0.98, P = 0.008), regardless of HoR status. No significant PFS differences were found.

CONCLUSIONS

Compared with HER2-zero status, HER2-low status appears to be associated with a slightly increased OS both in the advanced and early settings, regardless of HoR expression. In the early setting, HER2-low tumours seem to be associated to lower pCR rates, especially if HoR-positive.

Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis

BACKGROUND

In hormone receptor-positive (HoR+) breast cancer (BC), gene expression analysis identifies luminal A (LumA), luminal B (LumB), human epidermal growth factor receptor 2 (HER2)-enriched (HER2-E), basal-like (BL) intrinsic subtypes and a normal-like group. This classification has an established prognostic value in early-stage HoR+ BC. Here, we carried out a trial-level meta-analysis to determine the prognostic ability of subtypes in metastatic BC (MBC).

MATERIALS AND METHODS

We systematically reviewed all the available prospective phase II/III trials in HoR+ MBC where subtype was assessed. The primary endpoint was progression-free survival (PFS)/time to progression (TTP) of the LumA subtype compared to non-LumA. Secondary endpoints were PFS/TTP of each individual subtype, according to treatment, menopausal and HER2 status and overall survival (OS). The random-effect model was applied, and heterogeneity assessed through Cochran's Q and I². Threshold for significance was set at P < 0.05. The study was registered in PROSPERO (ID: CRD42021255769).

RESULTS

Seven studies were included (2536 patients). Non-LumA represented 55.2% and was associated with worse PFS/TTP than LumA [hazard ratio (HR) 1.77, P < 0.001, I² = 61%], independently of clinical HER2 status [P_{subgroup difference} (P_sub) = 0.16], systemic treatment (P_sub = 0.96) and menopausal status (P_sub = 0.12). Non-LumA tumors also showed worse OS (HR 2.00, P < 0.001, I² = 65%), with significantly different outcomes for LumB (PFS/TTP HR 1.46; OS HR 1.41), HER2-E (PFS/TTP HR 2.39; OS HR 2.08) and BL (PFS/TTP HR 2.67; OS HR 3.26), separately (PFS/TTP P_sub = 0.01; OS P_sub = 0.005). Sensitivity analyses supported the main result. No publication bias was observed.

CONCLUSIONS

In HoR+ MBC, non-LumA disease is associated with poorer PFS/TTP and OS than LumA, independently of HER2, treatment and menopausal status. Future trials in HoR+ MBC should consider this clinically relevant biological classification.

Molecular Profiling in Early ER + Breast Cancer to Aid Systemic Therapy Decisions

PURPOSE OF REVIEW

Clinical decisions for (neo)adjuvant treatment in early breast cancer (eBC) have been based mostly on clinical factors over the last decades. We have reviewed development and validation of such assays in the HR + /HER2 eBC and discuss possible future directions in this field.

RECENT FINDINGS

Increasing knowledge about the biology of hormone-sensitive eBC, based on the precise and reproducible multigene expression analysis, has led to a significant change in the treatment pathways and reduction of overtreatment in particular by chemotherapy in HR + /HER2 eBC with up to 3 positive lymph nodes based on results from several retrospective-prospective trials used several genomic assays and in particular prospective trials (TAILORx, RxPonder, MINDACT, and ADAPT used OncotypeDX® and Mammaprint®). Precise evaluation of tumor biology together with endocrine responsiveness assessment appears as promising tools for individualized treatment decisions together with clinical factors and menopausal status in early hormone-sensitive/HER2-negative breast cancer.

The effect of non-oncology drugs on clinical and genomic risk in early luminal breast cancer

BACKGROUND

An effect of non-oncology medications on cancer outcome has been proposed. In this study, we aimed to systematically examine the impact of commonly prescribed non-oncology drugs on clinical risk and on the genomic risk [based on the Oncotype DX recurrence score (RS)] in early breast cancer (BC).

EXPERIMENTAL DESIGN

We collected data on clinical risk (stage and grade), genomic risk (Oncotype DX RS), and on non-oncology medications administered to 1423 patients with estrogen receptor-positive human epidermal growth factor receptor 2-negative BC during the month of their surgery. The influence of various medications on clinical and genomic risks was evaluated by statistical analysis.

RESULTS

Out of the multiple drugs we examined, levothyroxine was significantly associated with a high Oncotype DX RS (mean 24.78; P < 0.0001) and metformin with a low Oncotype DX RS (mean 14.87; P < 0.01) compared with patients not receiving other non-oncology drugs (mean 18.7). By contrast, there were no differences in the clinical risk between patients receiving metformin, levothyroxine, or no other non-oncology drugs. Notably, there was no association between the consumption of levothyroxine and metformin and proliferation marker (Ki67) levels, but both drugs were significantly associated with progesterone-related features, suggesting that they influence genomic risk through estrogen-dependent signaling.

CONCLUSIONS

The results of this study indicate a significant impact of metformin and levothyroxine on clinical decisions in luminal BC, with potential impact on the clinical course of these patients.

Clinical Validation of EndoPredict in Pre-Menopausal Women with ER-Positive, HER2-Negative Primary Breast Cancer

PURPOSE

The EndoPredict prognostic assay is validated to predict distant recurrence and response to chemotherapy primarily in post-menopausal women with estrogen receptor-positive (ER+), HER2- breast cancer. This study evaluated the performance of EndoPredict in pre-menopausal women.

EXPERIMENTAL DESIGN

Tumor samples from 385 pre-menopausal women with ER+, HER2- primary breast cancer (pT1-3, pN0-1) who did not receive chemotherapy in addition to endocrine therapy were tested with EndoPredict to produce a 12-gene EP molecular score and an integrated EPclin score that includes pathologic tumor size and nodal status. Associations of molecular and EPclin scores with 10-year distant recurrence-free survival (DRFS) were evaluated by Cox proportional hazards models and Kaplan-Meier analysis.

RESULTS

After a median follow-up of 9.7 years, both the EP molecular score and the molecular-clinicopathologic EPclin score were associated with increased risk of distant recurrence [HR, 1.33; 95% confidence interval (CI), 1.18-1.50; P = 7.2 × 10-6; HR, 3.58; 95% CI, 2.26-5.66; P = 9.8 × 10-8, respectively]. Both scores remained significant after adjusting for clinical factors in multivariate analysis. Patients with low-risk EPclin scores (64.7%) had significantly improved DRFS compared with high-risk patients (HR, 4.61; 95% CI, 1.40-15.17; P = 4.2 × 10-3). At 10 years, patients with low-risk and high-risk EPclin scores had a DRFS of 97% (95% CI, 93%-99%) and 76% (95% CI, 67%-82%), respectively.

CONCLUSIONS

The EPclin score is strongly associated with DRFS in pre-menopausal women who received adjuvant endocrine therapy alone. On the basis of these data, pre-menopausal women with EPclin low-risk breast cancer may be treated with endocrine therapy only and safely forgo adjuvant chemotherapy.

pH-Responsive PEGylated Niosomal Nanoparticles as an Active-Targeting Cyclophosphamide Delivery System for Gastric Cancer Therapy

A PEGylated niosomal formulation of cyclophosphamide (Nio-Cyclo-PEG) was prepared using a central composite design and characterized in terms of drug loading, size distribution, and average size. The stability of formulations was also studied at different conditions. In vitro cytotoxicity of drug delivery formulations was assessed on gastric cancer cells using MTT assay. The mechanism of cytotoxicity was studied at the transcriptional level by real-time PCR on Caspase3, Caspase9, CyclinD, CyclinE, MMP-2, and MMP-9 genes, while apoptosis was investigated with flow cytometry. The anti-metastatic property was evaluated using the scratch method. Propidium iodide staining was used to study the cell cycle. The results indicated that the as-designed nanocarrier exhibited a controlled drug release pattern with improved nanoparticle stability. It was found that the living cancer cells treated with Nio-Cyclo-PEG showed a significant decrease in number when compared with the niosomal carrier without PEG (Nio-Cyclo) and free drug (Cyclo). Moreover, the drug-loaded nanocarrier induced planned death (apoptosis) in the cancer cells through the regulation of Caspase3, Caspase9, CyclinD, CyclinE, MMP-9, and MMP-2 gene expression, indicating that the Nio-Cyclo-PEG formulation could significantly inhibit the cell cycle at the sub G1 phase as well as prevent the migration of cancer cells. In conclusion, Nio-Cyclo-PEG as developed in this study could serve as an active-targeting drug delivery nanocarriers for gastric cancer therapy with high efficacy and minimal side effects on healthy tissues/cells.

Neither Tumor-Infiltrating Lymphocytes nor Cytotoxic T Cells Predict Enhanced Benefit from Chemotherapy in the DBCG77B Phase III Clinical Trial

Simple Summary

Apart from the direct killing of cancer cells, cyclophosphamide-based chemotherapy has been shown to induce an antitumor immune response, and is being used in combination with immunotherapies in cancer care. We assessed the interaction of chemotherapy with immune biomarkers expressed on primary tumor tissue from a randomized phase III clinical trial, and confirmed that the presence of tumor-infiltrating lymphocytes is linked to improved survival in premenopausal women with high-risk breast cancer, regardless of their treatment allocation. However, immune biomarkers including tumor-infiltrating lymphocytes do not predict extra benefit from cyclophosphamide chemotherapy. This finding applies across the major molecular subgroups, including non-luminal and basal breast cancers that tend to be more immunogenic, and are often considered the most suitable subsets for receiving immunotherapy.

Abstract

Recent studies have shown that immune infiltrates in the tumor microenvironment play a role in response to therapy, with some suggesting that patients with immunogenic tumors may receive increased benefit from chemotherapies. We evaluated this hypothesis in early breast cancer by testing the interaction between immune biomarkers and chemotherapy using materials from DBCG77B, a phase III clinical trial where high-risk premenopausal women were randomized to receive chemotherapy or no chemotherapy. Tissue microarrays were evaluated for tumor-infiltrating lymphocytes (TILs) assessed morphologically on hematoxylin and eosin-stained slides, and by immunohistochemistry for CD8, FOXP3, LAG-3, PD-1 and PD-L1. Following REMARK reporting guidelines, data analyses were performed according to a prespecified statistical plan, using 10-year invasive disease-free survival as the endpoint. Differences in survival probabilities between biomarker groups were evaluated by Kaplan–Meier and Cox proportional hazard ratio analyses and prediction for treatment benefit by an interaction test. Our results showed that stromal TILs were associated with an improved prognosis (HR = 0.93; p-value = 0.03), consistent with previous studies. However, none of the immune biomarkers predicted benefit from chemotherapy in the full study set nor within major breast cancer subtypes. Our study indicates that primary tumors with higher immune infiltration do not derive extra benefit from cyclophosphamide-based cytotoxic chemotherapy.

PAM50 subtyping and ROR score add long-term prognostic information in premenopausal breast cancer patients

PAM50 intrinsic subtyping and risk of recurrence (ROR) score are approved for risk profiling in postmenopausal women. We aimed to examine their long-term prognostic value in terms of breast cancer-free interval (BCFi) and overall survival (OS) (n = 437) in premenopausal women randomised to 2 years of tamoxifen versus no systemic treatment irrespective of hormone-receptor status. Intrinsic subtyping added independent prognostic information in patients with oestrogen receptor-positive/human epidermal growth factor 2-negative tumours for BCFi and OS after maximum follow-up (overall P-value 0.02 and 0.006, respectively) and those with high versus low ROR had worse prognosis (maximum follow-up: hazard ratio (HR)_BCFi: 1.70, P = 0.04). The prognostic information by ROR was similar regarding OS and in multivariable analysis. These results support that PAM50 subtyping and ROR score provide long-term prognostic information in premenopausal women. Moreover, tamoxifen reduced the incidence of breast cancer events only in patients with Luminal A_PAM50 tumours (0–10 years: HR_{BCFi(Luminal A)}: 0.41, HR_{BCFi(Luminal B)}: 1.19, P_interaction = 0.02).

Trial registration: This trial is registered in the ISRCTN database, trial ID: ISRCTN12474687.

Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update

PURPOSE

To update recommendations on appropriate use of breast cancer biomarker assay results to guide adjuvant endocrine and chemotherapy decisions in early-stage breast cancer.

METHODS

An updated literature search identified randomized clinical trials and prospective-retrospective studies published from January 2016 to October 2021. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert Panel members used informal consensus to develop evidence-based recommendations.

RESULTS

The search identified 24 studies informing the evidence base.

RECOMMENDATIONS

Clinicians may use Oncotype DX, MammaPrint, Breast Cancer Index (BCI), and EndoPredict to guide adjuvant endocrine and chemotherapy in patients who are postmenopausal or age > 50 years with early-stage estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative (ER+ and HER2-) breast cancer that is node-negative or with 1-3 positive nodes. Prosigna and BCI may be used in postmenopausal patients with node-negative ER+ and HER2- breast cancer. In premenopausal patients, clinicians may use Oncotype in patients with node-negative ER+ and HER2- breast cancer. Current data suggest that premenopausal patients with 1-3 positive nodes benefit from chemotherapy regardless of genomic assay result. There are no data on use of genomic tests to guide adjuvant chemotherapy in patients with ≥ 4 positive nodes. Ki67 combined with other parameters or immunohistochemistry 4 score may be used in postmenopausal patients without access to genomic tests to guide adjuvant therapy decisions. BCI may be offered to patients with 0-3 positive nodes who received 5 years of endocrine therapy without evidence of recurrence to guide decisions about extended endocrine therapy. None of the assays are recommended for treatment guidance in individuals with HER2-positive or triple-negative breast cancer. Treatment decisions should also consider disease stage, comorbidities, and patient preferences.Additional information is available at www.asco.org/breast-cancer-guidelines.

Clinical Utility of Multigene Profiling Assays in Early-Stage Invasive Breast Cancer: An Ontario Health (Cancer Care Ontario) Clinical Practice Guideline

OBJECTIVE

The purpose of this guideline is to determine the clinical utility of multigene profiling assays in individuals with early-stage invasive breast cancer.

METHODS

This guideline was developed by Ontario Health (Cancer Care Ontario)'s Program in Evidence-Based Care (PEBC) through a systematic review of relevant literature, patient- and caregiver-specific consultation and internal and external reviews. Recommendation 1: In patients with early-stage estrogen receptor (ER)-positive/human epidermal growth factor 2 (HER2)-negative breast cancer, clinicians should consider using multigene profiling assays (i.e., Oncotype DX, MammaPrint, Prosigna, EndoPredict, and the Breast Cancer Index) to help guide the use of systemic therapy. Recommendation 2: In patients with early-stage node-negative ER-positive/HER2-negative disease, clinicians may use a low-risk result from Oncotype DX, MammaPrint, Prosigna, EndoPredict/EPclin, or Breast Cancer Index assays to support a decision not to use adjuvant chemotherapy. Recommendation 3: In patients with node-negative ER-positive/HER2-negative disease, clinicians may use a high-risk result from Oncotype DX to support a decision to offer chemotherapy. A high Oncotype DX recurrence score is capable of predicting adjuvant chemotherapy benefit. Recommendation 4: In postmenopausal patients with ER-positive/HER2-negative tumours and one to three nodes involved (N1a disease), clinicians may withhold chemotherapy based on a low-risk Oncotype DX or MammaPrint score if the decision is supported by other clinical, pathological, or patient-related factors. Recommendation 5: The evidence to support the use of molecular profiling to select the duration of endocrine therapy is evolving. In patients with ER-positive disease, clinicians may consider using a Breast Cancer Index (H/I) high assay result to support a decision to extend adjuvant endocrine therapy if the decision is supported by other clinical, pathological, or patient-related factors.

Intrinsic subtypes in Ethiopian breast cancer patient

PURPOSE

The recent development of multi-gene assays for gene expression profiling has contributed significantly to the understanding of the clinically and biologically heterogeneous breast cancer (BC) disease. PAM50 is one of these assays used to stratify BC patients and individualize treatment. The present study was conducted to characterize PAM50-based intrinsic subtypes among Ethiopian BC patients.

PATIENTS AND METHODS

Formalin-fixed paraffin-embedded tissues were collected from 334 BC patients who attended five different Ethiopian health facilities. All samples were assessed using the PAM50 algorithm for intrinsic subtyping.

RESULTS

The tumor samples were classified into PAM50 intrinsic subtypes as follows: 104 samples (31.1%) were luminal A, 91 samples (27.2%) were luminal B, 62 samples (18.6%) were HER2-enriched and 77 samples (23.1%) were basal-like. The intrinsic subtypes were found to be associated with clinical and histopathological parameters such as steroid hormone receptor status, HER2 status, Ki-67 proliferation index and tumor differentiation, but not with age, tumor size or histological type. An immunohistochemistry-based classification of tumors (IHC groups) was found to correlate with intrinsic subtypes.

CONCLUSION

The distribution of the intrinsic subtypes confirms previous immunohistochemistry-based studies from Ethiopia showing potentially endocrine-sensitive tumors in more than half of the patients. Health workers in primary or secondary level health care facilities can be trained to offer endocrine therapy to improve breast cancer care. Additionally, the findings indicate that PAM50-based classification offers a robust method for the molecular classification of tumors in the Ethiopian context.

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

OBJECTIVE

To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects.

DESIGN

Scoping review.

METHODS

We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests.

RESULTS

Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.

CONCLUSIONS

While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies.

Advancement of prognostic models in breast cancer: a narrative review

Objective

To provide a reference for clinical work and guide the decision-making of healthcare providers and end-users, we systematically reviewed the development, validation and classification of classical prognostic models for breast cancer.

Background

Patients suffering from breast cancer have different prognosis for its high heterogeneity. Accurate prognosis prediction and risk stratification for breast cancer are crucial for individualized treatment. There is a lack of systematic summary of breast cancer prognostic models.

Methods

We conducted a PubMed search with keywords "breast neoplasm", "prognostic model", "recurrence" and "metastasis", and screened the retrieved publications at three levels: title, abstract and full text. We identified the articles presented the development and/or validation of models based on clinicopathological factors, genomics, and machine learning (ML) methods to predict survival and/or benefits of adjuvant therapy in female breast cancer patients.

Conclusions

Combining prognostic-related variables with long-term clinical outcomes, researchers have developed a series of prognostic models based on clinicopathological parameters, genomic assays, and medical figures. The discrimination, calibration, overall performance, and clinical usefulness were validated by internal and/or external verifications. Clinicopathological models integrated the clinical parameters, including tumor size, histological grade, lymph node status, hormone receptor status to provide prognostic information for patients and doctors. Gene-expression assays deeply revealed the molecular heterogeneity of breast cancer, some of which have been cited by AJCC and National Comprehensive Cancer Network (NCCN) guidelines. In addition, the models based on the ML methods provided more detailed information for prognosis prediction by increasing the data dimension. Combined models incorporating clinical variables and genomics information are still required to be developed as the focus of further researches.

Prediction of Late Recurrence and Distant Metastasis in Early-stage Breast Cancer: Overview of Current and Emerging Biomarkers

Recently, a significant number of breast cancer (BC) patients have been diagnosed at an early stage. It is therefore critical to accurately predict the risk of recurrence and distant metastasis for better management of BC in this setting. Clinicopathologic patterns, particularly lymph node status, tumor size, and hormonal receptor status are routinely used to identify women at increased risk of recurrence. However, these factors have limitations regarding their predictive ability for late metastasis risk in patients with early BC. Emerging molecular signatures using gene expression-based approaches have improved the prognostic and predictive accuracy for this indication. However, the use of their based-scores for risk assessment has provided contradictory findings. Therefore, developing and using newly emerged alternative predictive and prognostic biomarkers for identifying patients at high- and low-risk is of great importance. The present review discusses some serum biomarkers and multigene profiling scores for predicting late recurrence and distant metastasis in early-stage BC based on recently published studies and clinical trials.

Gene expression profiling of perineural invasion in head and neck cutaneous squamous cell carcinoma

Perineural invasion (PNI) is frequently associated with aggressive clinical behaviour in head and neck cutaneous squamous cell carcinoma (HNcSCC) leading to local recurrence and treatment failure. This study evaluates the gene expression profiles of HNcSCC with PNI using a differential expression analysis approach and constructs a tailored gene panel for sensitivity and specificity analysis. 45 cases of HNcSCC were stratified into three groups (Extensive, Focal and Non PNI) based on predefined clinicopathological criteria. Here we show HNcSCC with extensive PNI demonstrates significant up- and down-regulation of 144 genes associated with extracellular matrix interactions, epithelial to mesenchymal transition, cell adhesion, cellular motility, angiogenesis, and cellular differentiation. Gene expression of focal and non PNI cohorts were indistinguishable and were combined for further analyses. There is clinicopathological correlation between gene expression analysis findings and disease behaviour and a tailored panel of 10 genes was able to identify extensive PNI with 96% sensitivity and 95% specificity.

The Detection and Bioinformatic Analysis of Alternative 3' UTR Isoforms as Potential Cancer Biomarkers

Alternative transcript cleavage and polyadenylation is linked to cancer cell transformation, proliferation and outcome. This has led researchers to develop methods to detect and bioinformatically analyse alternative polyadenylation as potential cancer biomarkers. If incorporated into standard prognostic measures such as gene expression and clinical parameters, these could advance cancer prognostic testing and possibly guide therapy. In this review, we focus on the existing methodologies, both experimental and computational, that have been applied to support the use of alternative polyadenylation as cancer biomarkers.

Challenges in Adjuvant Therapy for Premenopausal Women Diagnosed With Luminal Breast Cancers

More than 90% of women with newly diagnosed breast cancer present with stage I to III disease and, with optimal multidisciplinary therapy, are likely to survive their disease. Of these patients, 70% are hormone receptor-positive and candidates for adjuvant endocrine therapy. The adoption of cumulatively better adjuvant treatments contributed to improved outcomes in patients with hormone receptor-positive, early-stage breast cancer. Premenopausal women with hormone receptor-positive breast cancer often present with complex disease and have inferior survival outcomes compared with their postmenopausal counterparts. Risk stratification strategies, including classic clinicopathologic features and newer gene expression assays, can assist in treatment decisions, including adjuvant chemotherapy use and type or duration of endocrine therapy. Gene expression assays may help identify patients who can safely forgo chemotherapy, although to a lesser extent among premenopausal patients, in whom they may play a role only in node-negative disease. Patients at lower risk of recurrence can be adequately treated with tamoxifen alone, whereas higher-risk patients benefit from ovarian function suppression with tamoxifen or an aromatase inhibitor. The role of adding newer therapies such as CDK4/6 inhibitors to adjuvant endocrine therapy is not yet clear. Breast cancer treatments are associated with several side effects, with major impact on patients' quality of life and treatment adherence, particularly in premenopausal women for whom these side effects may be more prominent as the result of the abrupt decrease in estrogen concentrations. Personalized management of treatment side effects, addressing patients' concerns, and health promotion should be an integral part of the care of premenopausal women diagnosed with luminal breast cancers.

Differential and longitudinal immune gene patterns associated with reprogrammed microenvironment and viral mimicry in response to neoadjuvant radiotherapy in rectal cancer

BACKGROUND

Rectal cancers show a highly varied response to neoadjuvant radiotherapy/chemoradiation (RT/CRT) and the impact of the tumor immune microenvironment on this response is poorly understood. Current clinical tumor regression grading systems attempt to measure radiotherapy response but are subject to interobserver variation. An unbiased and unique histopathological quantification method (change in tumor cell density (ΔTCD)) may improve classification of RT/CRT response. Furthermore, immune gene expression profiling (GEP) may identify differences in expression levels of genes relevant to different radiotherapy responses: (1) at baseline between poor and good responders, and (2) longitudinally from preradiotherapy to postradiotherapy samples. Overall, this may inform novel therapeutic RT/CRT combination strategies in rectal cancer.

METHODS

We generated GEPs for 53 patients from biopsies taken prior to preoperative radiotherapy. TCD was used to assess rectal tumor response to neoadjuvant RT/CRT and ΔTCD was subjected to k-means clustering to classify patients into different response categories. Differential gene expression analysis was performed using statistical analysis of microarrays, pathway enrichment analysis and immune cell type analysis using single sample gene set enrichment analysis. Immunohistochemistry was performed to validate specific results. The results were validated using 220 pretreatment samples from publicly available datasets at metalevel of pathway and survival analyses.

RESULTS

ΔTCD scores ranged from 12.4% to -47.7% and stratified patients into three response categories. At baseline, 40 genes were significantly upregulated in poor (n=12) versus good responders (n=21), including myeloid and stromal cell genes. Of several pathways showing significant enrichment at baseline in poor responders, epithelial to mesenchymal transition, coagulation, complement activation and apical junction pathways were validated in external cohorts. Unlike poor responders, good responders showed longitudinal (preradiotherapy vs postradiotherapy samples) upregulation of 198 immune genes, reflecting an increased T-cell-inflamed GEP, type-I interferon and macrophage populations. Longitudinal pathway analysis suggested viral-like pathogen responses occurred in post-treatment resected samples compared with pretreatment biopsies in good responders.

CONCLUSION

This study suggests potentially druggable immune targets in poor responders at baseline and indicates that tumors with a good RT/CRT response reprogrammed from immune "cold" towards an immunologically "hot" phenotype on treatment with radiotherapy.

Validation of the GenesWell BCT Score in Young Asian Women With HR+/HER2- Early Breast Cancer

Background

The prognostic or predictive value of commonly used multigene assays in young patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer is unclear. In this study, we assessed the prognostic value of the GenesWell BCT assay according to age group.

Methods

We identified patients with pN0-1, HR+/HER2- breast cancer in a prospective cohort of women who underwent surgery between 2005 and 2017. The GenesWell BCT assay was performed on tissue samples from selected patients. Distant metastasis-free survival (DMFS) and disease-free survival (DFS) were compared between the risk groups assigned by the BCT score.

Results

A total of 712 patients were eligible for analysis. The median follow-up time was 7.47 years. The BCT score was prognostic in patients aged ≤50 years (n = 404) and those aged >50 years (n = 308). In both age groups, the 10-year DMFS and DFS rates for patients classified as high risk by the BCT score were significantly lower than those for patients classified as low risk. A multivariate analysis revealed that the BCT score was an independent prognostic factor for DFS in patients aged ≤50 years (hazard ratio, 1.28; 95% CI, 1.05-1.56; P = 0.015), as well as those aged >50 years.

Conclusion

The BCT score could be used to identify low-risk patients who will not benefit from adjuvant chemotherapy to treat HR+/HER2- early breast cancer regardless of age. A further prospective study to assess the prognostic and predictive value of the BCT score is required.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

Epigenetics in Breast Cancer Therapy-New Strategies and Future Nanomedicine Perspectives

Epigenetic dysregulation has been recognized as a critical factor contributing to the development of resistance against standard chemotherapy and to breast cancer progression via epithelial-to-mesenchymal transition. Although the efficacy of the first-generation epigenetic drugs (epi-drugs) in solid tumor management has been disappointing, there is an increasing body of evidence showing that epigenome modulation, in synergy with other therapeutic approaches, could play an important role in cancer treatment, reversing acquired therapy resistance. However, the epigenetic therapy of solid malignancies is not straightforward. The emergence of nanotechnologies applied to medicine has brought new opportunities to advance the targeted delivery of epi-drugs while improving their stability and solubility, and minimizing off-target effects. Furthermore, the omics technologies, as powerful molecular epidemiology screening tools, enable new diagnostic and prognostic epigenetic biomarker identification, allowing for patient stratification and tailored management. In combination with new-generation epi-drugs, nanomedicine can help to overcome low therapeutic efficacy in treatment-resistant tumors. This review provides an overview of ongoing clinical trials focusing on combination therapies employing epi-drugs for breast cancer treatment and summarizes the latest nano-based targeted delivery approaches for epi-drugs. Moreover, it highlights the current limitations and obstacles associated with applying these experimental strategies in the clinics.

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.

Predictive Value of Molecular Subtypes in Premenopausal Women with Hormone Receptor-positive Early Breast Cancer: Results from the ABCSG Trial 5

PURPOSE

To assess the predictive value of molecular breast cancer subtypes in premenopausal patients with hormone receptor-positive early breast cancer who received adjuvant endocrine treatment or chemotherapy.

EXPERIMENTAL DESIGN

Molecular breast cancer subtypes were centrally assessed on whole tumor sections by IHC in patients of the Austrian Breast and Colorectal Cancer Study Group Trial 5 who had received either 5 years of tamoxifen/3 years of goserelin or six cycles of cyclophosphamide, methotrexate, and fluorouracil (CMF). Luminal A disease was defined as Ki67 <20% and luminal B as Ki67 ≥20%. The luminal B/HER2-positive subtype displayed 3+ HER2-IHC or amplification by ISH. Recurrence-free survival (RFS) and overall survival (OS) were analyzed using Cox models adjusted for clinical and pathologic factors.

RESULTS

185 (38%), 244 (50%), and 59 (12%) of 488 tumors were classified as luminal A, luminal B/HER2-negative and luminal B/HER2-positive, respectively. Luminal B subtypes were associated with poor outcome. Patients with luminal B tumors had a significantly shorter RFS [adjusted HR for recurrence: 2.22; 95% confidence interval (CI), 1.41-3.49; P = 0.001] and OS (adjusted HR for death: 3.51; 95% CI, 1.80-6.87; P < 0.001). No interaction between molecular subtypes and treatment was observed (test for interaction: P = 0.84 for RFS; P = 0.69 for OS).

CONCLUSIONS

Determination of molecular subtypes by IHC is an independent prognostic factor for recurrence and death in premenopausal women with early-stage, hormone receptor-positive breast cancer but is not predictive for outcome of adjuvant treatment with tamoxifen/goserelin or CMF.See related commentary by Hunter et al., p. 5543.

Gene Expression Profiling Tests for Early-Stage Invasive Breast Cancer: A Health Technology Assessment

BACKGROUND

Breast cancer is a disease in which cells in the breast grow out of control. They often form a tumour that may be seen on an x-ray or felt as a lump.Gene expression profiling (GEP) tests are intended to help predict the risk of metastasis (spread of the cancer to other parts of the body) and to identify people who will most likely benefit from chemotherapy. We conducted a health technology assessment of four GEP tests (EndoPredict, MammaPrint, Oncotype DX, and Prosigna) for people with early-stage invasive breast cancer, which included an evaluation of effectiveness, safety, cost effectiveness, the budget impact of publicly funding GEP tests, and patient preferences and values.

METHODS

We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using either the Cochrane Risk of Bias tool, Prediction model Risk Of Bias ASsessment Tool (PROBAST), or Risk of Bias Assessment tool for Non-randomized Studies (RoBANS), depending on the type of study and outcome of interest, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also performed a literature survey of the quantitative evidence of preferences and values of patients and providers for GEP tests.We performed an economic evidence review to identify published studies assessing the cost-effectiveness of each of the four GEP tests compared with usual care or with one another for people with early-stage invasive breast cancer. We adapted a decision-analytic model to compare the costs and outcomes of care that includes a GEP test with usual care without a GEP test over a lifetime horizon. We also estimated the budget impact of publicly funding GEP tests to be conducted in Ontario, compared with funding tests conducted through the out-of-country program and compared with no funding of tests in any location.To contextualize the potential value of GEP tests, we spoke with people who have been diagnosed with early-stage invasive breast cancer.

RESULTS

We included 68 studies in the clinical evidence review. Within the lymph-node-negative (LN-) population, GEP tests can prognosticate the risk of distant recurrence (GRADE: Moderate) and may predict chemotherapy benefit (GRADE: Low). The evidence for prognostic and predictive ability (ability to indicate the risk of an outcome and ability to predict who will benefit from chemotherapy, respectively) was lower for the lymph-node-positive (LN+) population (GRADE: Very Low to Low). GEP tests may also lead to changes in treatment (GRADE: Low) and generally may increase physician confidence in treatment recommendations (GRADE: Low).Our economic evidence review showed that GEP tests are generally cost-effective compared with usual care.Our primary economic evaluation showed that all GEP test strategies were more effective (led to more quality-adjusted life-years [QALYs]) than usual care and can be considered cost-effective below a willingness-to-pay of $20,000 per QALY gained. There was some uncertainty in our results. At a willingness-to-pay of $50,000 per QALY gained, the probability of each test being cost-effective compared to usual care was 63.0%, 89.2%, 89.2%, and 100% for EndoPredict, MammaPrint, Oncotype DX, and Prosigna, respectively.Sensitivity analyses showed our results were robust to variation in subgroups considered (i.e., LN+ and premenopausal), discount rates, age, and utilities. However, cost parameter assumptions did influence our results. Our scenario analysis comparing tests showed Oncotype DX was likely cost-effective compared with MammaPrint, and Prosigna was likely cost-effective compared with EndoPredict. When the GEP tests were compared with a clinical tool, the cost-effectiveness of the tests varied. Assuming a higher uptake of GEP tests, we estimated the budget impact to publicly fund GEP tests in Ontario would be between $1.29 million (Year 1) and $2.22 million (Year 5) compared to the current scenario of publicly funded GEP tests through the out-of-country program.Gene expression profiling tests are valued by patients and physicians for the additional information they provide for treatment decision-making. Patients are satisfied with what they learn from GEP tests and feel GEP tests can help reduce decisional uncertainty and anxiety.

CONCLUSIONS

Gene expression profiling tests can likely prognosticate the risk of distant recurrence and some tests may also predict chemotherapy benefit. In people with breast cancer that is ER+, LN-, and human epidermal growth factor receptor 2 (HER2)-negative, GEP tests are likely cost-effective compared with no testing. The GEP tests are also likely cost-effective in LN+ and premenopausal people. Compared with funding GEP tests through the out-of-country program, publicly funding GEP tests in Ontario would cost an additional $1 million to $2 million annually, assuming a higher uptake of tests. GEP tests are valued by both patients and physicians for chemotherapy treatment decision-making.

The Prosigna 50-gene profile and responsiveness to adjuvant anthracycline-based chemotherapy in high-risk breast cancer patients

The DBCG89D trial randomized high-risk early breast cancer patients to adjuvant CMF (cyclophosphamide, methotrexate and fluorouracil) or CEF (cyclophosphamide, epirubicin and fluorouracil). Prosigna assays were performed by researchers with no access to clinical data. Time to distant recurrence (DR) was the primary endpoint, time to recurrence (TR) and overall survival (OS) secondary. Among the 980 Danish patients enrolled, Prosigna results were obtained in 686. Continuous ROR score was associated with DR for CMF (adjusted hazard ratio (HR) 1.20, 95% CI 1.09-1.33), and for CEF (HR 1.04, 95% CI 0.92-1.18), P interaction = 0.06. DR was significantly longer in CEF compared to CMF treated patients with Her2-enriched tumors (HR 0.58, 95% CI 0.38-0.86), but not in patients with luminal tumors. Heterogeneity of treatment effect was significant for TR and OS. In this prospective-retrospective analysis, patients with Her2-enriched breast cancer derived substantial benefit from anthracycline chemotherapy whereas anthracyclines are not an essential component of chemotherapy for patients with luminal subtypes. The benefit of CEF vs. CMF correlated with increasing ROR Score.

Application of St Gallen Categories in Predicting Survival for Patients With Breast Cancer in Vietnam

Breast cancer is a heterogeneous disease with different tumor subtypes. Identifying risk categories will help make better treatment decisions. Hence, this study aimed to predict the survival outcomes of invasive breast cancer in Vietnam, using St Gallen 2007 classification. This study was conducted on 501 patients with breast cancer who had surgical operations, but had not received neoadjuvant chemotherapy, from 2011 to 2013. The clinicopathological characteristics were recorded. Immunohistochemistry staining was performed on ER, PR, HER2/neu, and Ki67 markers. For HER2/neu(2+), fluorescence in situ hybridization was used as the test. All patients with breast cancer were stratified according to 2007 St Gallen categories. Kaplan-Meier and log-rank models were used to analyze survival rates. There were 3.8% cases classified as low risk (LR), 72.1% as intermediate risk (IR1: 60.1% and IR2: 12.0%), and 24.1% as high risk (HR1: 11.8% and HR2: 12.3%). Patients who were LR had the best prognosis, with a 5-year overall survival (OS) rate of 100%. Intermediate-risk patients were at 92.3%. High-risk patients had the worst prognosis, with a 5-year OS proportion of 69.3% (P < .05). For disease-free survival (DFS), risk categories were categorized as LR: 100%, IR: 90.3%, and HR: 69.3% (P < .05). Three main risk categories of breast cancer had a distinct OS and DFS. These findings suggest that the 2007 St Gallen risk category could be used to stratify patients with breast cancer into different risk groups in Vietnam.

Emerging immune gene signatures as prognostic or predictive biomarkers in breast cancer

Several multigene assays have been developed to predict the risk of distant recurrence and response to adjuvant therapy in early breast cancer. However, the prognostic or predictive value of current proliferation gene signature-based assays are limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) early breast cancer. Considerable discordance between the different assays in classifying patients into risk groups has also been reported, thus raising questions about the clinical utility of these assays for individual patients. Therefore, there still remains a need for better prognostic or predictive biomarkers for breast cancer. The role of immune cells comprising tumor microenvironment in tumor progression has been recognized. Accumulating evidences have shown that immune gene signatures and tumor-infiltrating lymphocytes (TILs) can be prognostic or predictive factors in breast cancer, particularly with regard to HER2+ and triple-negative breast cancer. In this review, I summarize current multigene assays for breast cancer and discuss recent progress in identifying novel breast cancer biomarkers, focusing on the emerging importance of immune gene signatures and TILs as prognostic or predictive biomarkers.

Oral metronomic vinorelbine combined with endocrine therapy in hormone receptor-positive HER2-negative breast cancer: SOLTI-1501 VENTANA window of opportunity trial

Background

The biological effect of oral metronomic vinorelbine (mVNB) alone or in combination with endocrine therapy in patients with hormone receptor-positive (HR+)/HER2-negative breast cancer has been scarcely addressed.

Methods

Postmenopausal women with untreated stage I–III HR+/HER2-negative breast cancer were randomized (1:1:1) to receive 3 weeks of letrozole (LTZ) 2.5 mg/day, oral mVNB 50 mg 3 days/week, or the combination. The primary objective was to evaluate, within PAM50 Luminal A/B disease, if the anti-proliferative effect of LTZ+mVNB was superior to monotherapy. An anti-proliferative effect was defined as the mean relative decrease of the PAM50 11-gene proliferation score in combination arm vs. both monotherapy arms. Secondary objectives included the evaluation of a comprehensive panel of breast cancer-related genes and safety. An unplanned analysis of stromal tumor-infiltrating lymphocytes (sTILs) was also performed. PAM50 analyses were performed using the nCounter®-based Breast Cancer 360™ gene panel, which includes 752 genes and 32 signatures.

Results

Sixty-one patients were randomized, and 54 paired samples (89%) were analyzed. The main patient characteristics were mean age of 67, mean tumor size of 1.7 cm, mean Ki67 of 14.3%, stage I (55.7%), and grades 1–2 (90%). Most baseline samples were PAM50 Luminal A (74.1%) or B (22.2%). The anti-proliferative effect of 3 weeks of LTZ+mVNB (− 73.2%) was superior to both monotherapy arms combined (− 49.9%; p = 0.001) and mVNB (− 19.1%; p < 0.001). The anti-proliferative effect of LTZ+mVNB (− 73.2%) was numerically higher compared to LTZ (− 65.7%) but did not reach statistical significance (p = 0.328). LTZ+mVNB induced high expression of immune-related genes and gene signatures, including CD8 T cell signature and PDL1 gene and low expression of ER-regulated genes (e.g., progesterone receptor) and cell cycle-related and DNA repair genes. In tumors with ≤ 10% sTILs at baseline, a statistically significant increase in sTILs was observed following LTZ (paired analysis p = 0.049) and LTZ+mVNB (p = 0.012). Grade 3 adverse events occurred in 3.4% of the cases.

Conclusions

Short-term mVNB is well-tolerated and presents anti-proliferative activity alone and in combination with LTZ. The high expression of immune-related biological processes and sTILs observed with the combination opens the possibility of studying this combination with immunotherapy. Further investigation comparing these biological results with other metronomic schedules or drug combinations is warranted.

Trial registration

NCT02802748, registered 16 June 2016.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s13058-019-1195-z.

An integrative view on breast cancer signature panels

Introduction: Breast cancer is heterogeneous with distinct clinical outcomes. Diverse types of markers are available on the market for breast cancer prognosis, diagnosis, and therapeutics, with distinct assay approaches. These, though they enlarge our selection pool for characterizing breast cancer patients and help improve the precision on the therapeutics, they can complicate our understanding and choice of marker panels. Areas covered: This review aims at classifying the commonly used marker panels according to their functionalities and detection approaches, comparing their advantages and disadvantages, and identifying their shared features to gain a comprehensive understanding of the diversified molecular profiles that drive breast cancer heterogeneity. Expert opinion: Our effort will contribute as a guidebook for clinicians on the use of breast cancer signature panels for disease management, and for researchers on the establishment of novel marker panels with improved precision and reduced complexity. We propose that collectively analyzing all available marker panels is equally important as investigating on entirely novel marker panels. Advances in technologies capturing signals from multiple levels are of practical importance in breaking through limitations on translating markers into clinical use.

Avoiding over- and undertreatment in patients with resected node-positive breast cancer with the use of gene expression signatures: are we there yet?

Prediction of benefit from adjuvant chemotherapy following resection of early breast cancer and, as a result, proper selection of candidates remains an elusive goal since the relative magnitude of benefit is the same regardless of the presence of clinicopathologic factors. Multiple studies, including randomized trials, establish the role of certain gene expression signatures in node-negative disease since they predict the risk of breast cancer relapse being so low that adjuvant chemotherapy can be omitted. In contrast, more limited data are available in higher risk, node-positive breast cancer patients, making the exclusion of adjuvant chemotherapy potentially hazardous. 'Prospective-retrospective' studies and limited prospective data show that several signatures, namely Oncotype Dx, MammaPrint, Prosigna, EndoPredict and Breast Cancer Index, select with different levels of success node-positive patients at very low risk for distant recurrence despite not receiving chemotherapy, although the long-term follow-up is still awaited. Pending, however the publication of the results from ongoing randomized studies which enroll patients with node-positive disease, major caution is warranted. Improper use and misinterpretation of these transcriptomic profiles can lead to undertreatment and exposure of patients to unnecessary risks resulting in increased breast cancer mortality for patients with axillary node-positive disease. With this review we critically discuss the available data on gene expression signatures that are used in clinical practice and offer practical recommendations regarding the management of patients with ER-positive, human epidermal growth factor receptor 2 (HER2)-negative, node-positive breast cancer.

Summary of head-to-head comparisons of patient risk classifications by the 21-gene Recurrence Score® (RS) assay and other genomic assays for early breast cancer

Many genomic assays that assess recurrence risk in early breast cancer (EBC) are prognostic, but they differ in risk group stratification, which can affect clinical utility. Prospective outcomes of >60 K patients treated based on the 21-gene assay results have shown that chemotherapy may be safely omitted in EBC patents with low Recurrence Score (RS) results (RS < 18). Because of its extensive validation and wide clinical use, the RS assay is a common comparator in head-to-head studies with other assays. Published/presented studies of the RS assay performed on the same tumor samples with Breast Cancer Index (BCI), EndoPredict (EP) or EP+ clinical features (EPclin), MammaPrint (MMP) and/or Prosigna (ROR) assays were reviewed. Study findings were summarized descriptively.

SEOM clinical guidelines in early stage breast cancer (2018)

Breast cancer is the most common cancer in women in our country and it is usually diagnosed in the early and potentially curable stages. Nevertheless, around 20-30% of patients will relapse despite appropriate locoregional and systemic therapies. A better knowledge of this disease is improving our ability to select the most appropriate therapy for each patient with a recent diagnosis of an early stage breast cancer, minimizing unnecessary toxicities and improving long-term efficacy.

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.