Prognostic significance of ER-to-PR difference in ER+/HER2- early breast cancer

ER+/HER2- breast cancer is a common subtype of breast cancer. This study aimed to evaluate the prognostic value of ER-to-PR difference (EPD) in ER+/HER2- early breast cancer (EBC). A retrospective cohort study was conducted, including 3,340 ER+/HER2- EBC patients, divided into a training cohort of 2,873 patients and a validation cohort of 467 patients. The optimal EPD cutoff value for stratifying patients was determined using X-tile. Additionally, the prognostic value of EPD, when combined with other clinicopathological factors, was assessed using the Cox proportional hazards model and five traditional machine learning methods. The optimal cutoff value for EPD was determined as 10%, categorizing patients into EPD-low (ER-PR ≤ 10%) and EPD-high (ER-PR > 10%) expression groups. Patients with EPD-high tumors exhibited a poorer prognosis compared to those with EPD-low tumors. In the multivariate Cox model, EPD was identified as an independent prognostic factor for disease-free survival (DFS) (HR: 1.496, P = 0.004). Integrating EPD with clinicopathological parameters into a predictive model effectively predicts DFS in ER+/HER2- EBC patients. In the most effective CoxPH model, the area under the curve (AUC) values for predicting 3-year, 5-year, and 7-year DFS were 0.718, 0.702, and 0.701, respectively, in the WCH cohort, and 0.770, 0.739, and 0.743, respectively, in the FUSCC cohort. EPD may serve as a novel prognostic marker, allowing for the identification of a population with a poor prognosis in ER+/HER2- EBC, thereby aiding clinical decision-making.

Predicting invasive disease-free survival in ER-positive, HER2-negative early breast cancer using the PAM50 risk-of-recurrence score: a retrospective analysis using single-center long-term follow-up data of postmenopausal Japanese patients

BACKGROUND

The prognostic value of the risk-of-recurrence (ROR) score calculated using PAM50 has been validated using clinical trials and patient cohorts. This study aimed to investigate the prognostic value of the PAM50 ROR score in Japanese patients with early breast cancer using long-term follow-up data.

METHODS

We enrolled postmenopausal patients with ER-positive, HER2-negative, stage I-II breast cancer who had undergone surgery at the Kyoto University Hospital between 2008 and 2014. The intrinsic subtype and ROR score were calculated using PAM50. The primary endpoint was invasive disease-free survival (IDFS).

RESULTS

We enrolled 146 patients, of whom 47 (32%) patients had node-positive disease, and 36 (25%) had received neoadjuvant or adjuvant chemotherapy. The proportions of intrinsic subtypes for luminal A, luminal B, HER2-enriched, and basal-like subtypes were 67%, 27%, 3%, and 2%, respectively. The median follow-up duration was 8.4 (range 6.3-10.0) years, and 21 IDFS events were observed. Based on the ROR score, 37%, 33%, and 30% of the patients were classified as low, intermediate, and high risks, respectively. Patients in the high-risk group had a significantly worse 8-year IDFS rate than those in the low-to-intermediate-risk groups (75.1% vs. 91.6%, p = 0.04). The same trend was observed in patients with and without neoadjuvant or adjuvant chemotherapy.

CONCLUSIONS

Using long-term follow-up data, this study showed that the ROR score can predict the prognosis of ER-positive, HER2-negative early breast cancer in Japanese postmenopausal patients. Further investigations are required to confirm the prognostic value of the ROR score in Asian populations.

Evaluating the Prognostic Role of the PAM50 Signature and Selected Immune-Related Signatures for Recurrence in Patients With T1abN0 Breast Cancer

BACKGROUND

De-escalation of adjuvant treatment in patients with T1abN0 breast cancer is discussed internationally. Identification of new prognostic factors in these patients may assist this de-escalation. The PAM50 signature and tumor inflammation signature (TIS), Programmed Cell Death Protein 1 (PD-1) and Programmed Cell Death Ligand 1 (PD-L1) signatures are possible prognostic factors for recurrence.

MATERIALS AND METHODS

Danish patients with T1abN0 breast cancer diagnosed between 2007-2016 were identified, the NanoString Breast Cancer 360 Panel was performed on tissue samples from cases with recurrence matched 1:1 with controls without recurrence (n = 234). The association between gene signatures and recurrence was analyzed with conditional logistic regression.

RESULTS

Patients with the basal-like subtype had higher values of TIS, PD-1 and PD-L1 scores compared with other subtypes. Patients with higher PD-L1 score had significantly lower odds of recurrence (odds ratio [OR] 0.61, P = .01). Likewise, an increased TIS score was associated to lower, but nonsignificant odds of recurrence (OR 0.76, P = .07). Patients with human epidermal growth factor receptor 2 (HER2)-enriched subtype had significantly higher odds of recurrence compared with patients with luminal A subtype (OR 4.8, P = .03).

DISCUSSION

PAM50 and immune-related signatures provide important prognostic information in patients with T1abN0 breast cancer, which may refine the risk assessment in these 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.

Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay

PURPOSE

To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients categorized as intermediate risk based on classic clinicopathological variables and eligible for chemotherapy.

METHODS

In a case series comprising 234 invasive ER-positive/HER2-negative tumors, clinicopathological data including Prosigna results and corresponding HE-stained tissue slides were retrieved. The digitized HE slides were analysed by Stratipath Breast.

RESULTS

Our findings showed that the Stratipath Breast analysis identified 49.6% of the clinically intermediate tumors as low risk and 50.4% as high risk. The Prosigna assay classified 32.5%, 47.0% and 20.5% tumors as low, intermediate and high risk, respectively. Among Prosigna intermediate-risk tumors, 47.3% were stratified as Stratipath low risk and 52.7% as high risk. In addition, 89.7% of Stratipath low-risk cases were classified as Prosigna low/intermediate risk. The overall agreement between the two tests for low-risk and high-risk groups (N = 124) was 71.0%, with a Cohen's kappa of 0.42. For both risk profiling tests, grade and Ki67 differed significantly between risk groups.

CONCLUSION

The results from this clinical evaluation of image-based risk stratification shows a considerable agreement to an established gene expression assay in routine breast pathology.

Is the CTS5 a helpful decision-making tool in the extended adjuvant therapy setting?

PURPOSE

The Clinical Treatment Score post-5 years (CTS5) is an easy-to-use tool estimating the late distant recurrence (LDR) risk in patients with hormone receptor-positive breast cancer after 5 years of endocrine therapy (ET). Apart from evaluating the prognostic value and calibration accuracy of CTS5, the aim of this study is to clarify if this score is able to identify patients at higher risk for LDR who will benefit from extended ET.

METHODS

Prognostic power, calibration, and predictive value of the CTS5 was tested in patients of the prospective ABCSG-06 and -06a trials (n = 1254 and 860 patients, respectively). Time to LDR was analyzed with Cox regression models.

RESULTS

Higher rates of LDR in the years five to ten were observed in high- and intermediate-risk patients compared to low-risk patients (HR 4.02, 95%CI 2.26-7.15, p < 0.001 and HR 1.93, 95%CI 1.05-3.56, p = 0.035). An increasing continuous CTS5 was associated with increasing LDR risk (HR 2.23, 95% CI 1.74-2.85, p < 0.001). Miscalibration of CTS5 in high-risk patients could be observed. Although not reaching significance, high-risk patients benefitted the most from prolonged ET with an absolute reduction of the estimated 5-year LDR of - 6.1% (95%CI - 14.4 to 2.3).

CONCLUSION

The CTS5 is a reliable prognostic tool that is well calibrated in the lower and intermediate risk groups with a substantial difference of expected versus observed LDR rates in high-risk patients. While a numerical trend in favoring prolonged ET for patients with a higher CTS5 was found, a significantly predictive value for the score could not be confirmed.

CLINICAL TRIAL REGISTRATION

ABCSG-06 trial (NCT00309491), ABCSG-06A7 1033AU/0001 (NCT00300508).

Molecular subtyping improves breast cancer diagnosis in the Copenhagen Breast Cancer Genomics Study

BACKGROUNDIntrinsic molecular subtypes define distinct biological breast cancers and can be used to further improve diagnosis and risk allocation.METHODSThe Copenhagen Breast Cancer Genomics Study (CBCGS) prospectively included women diagnosed with breast cancer at Rigshospitalet from 2014 to 2021. Eligible patients were females with a primary invasive breast cancer (T1c, if N0M0; otherwise, any T, any N, or any M stage) and no prior malignancy. All patients underwent molecular profiling with the CIT256 and PAM50 molecular profile.RESULTSIn the study period, 2,816 patients were included in the CBCGS. Molecular subtyping showed an increase in nonluminal (molecular-apocrine, luminal C, and Basal-like) as compared with luminal (luminal A, luminal B, and Normal-like) subtypes with increasing stage from I to IV. Across all stages, we found a significant difference in survival among subtypes; 91% of patients with LumA were alive at 5 years compared with 91% for LumB, 84% for LumC, 82% for mApo, and 80% for Basal-like. We identified 442 tumors (16%) that were discordant in subtype between CIT256 and IHC. Discordant subtype proved to be a risk factor of death among patients with IHC luminal breast cancer (hazard ratio [HR], 2.08; 95% CI, 1.51-2.86) in a multivariable Cox regression analysis. Discordance occurred more often among patients with N3, stage IV, or grade III disease.CONCLUSIONOur findings indicate that molecular subtypes are a predominant classification for survival. Assessment is particularly crucial for patients with IHC luminal breast cancer with known high-risk factors, since they are at an increased risk of harboring an aggressive molecular subtype.

Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer

Combining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

Increased PI3K pathway activity is associated with recurrent breast cancer in patients with low and intermediate 21-gene recurrence score

AIMS

We investigated key signalling pathways' activity and mutational status of early-stage breast carcinomas with low and intermediate 21-gene recurrence score (RS) to identify molecular features that may predict recurrence.

METHODS

This is a retrospective case-control study of 18 patients with recurrent breast carcinoma with low and intermediate 21-gene RS (<25) and control group of 15 non-recurrent breast cancer patients. DNA and mRNA were extracted from tumour tissue. mRNA expression of genes involved in oestrogen receptor (ER), androgen receptor (AR), PI3K and MAPK signalling pathways was measured by real-time quantitative reverse transcription-qPCR (OncoSIGNal G4 test, InnoSIGN). Tumour mutational landscape was assessed by targeted DNA sequencing (Oncomine Precision Assay).

RESULTS

There were no statistical differences between the groups' demographic and clinicopathological characteristics. PI3K pathway showed significantly higher activity in cases compared with controls (p=0.0014). Receiver operating characteristic curve analysis showed an area under the curve of 0.79 for PI3K pathway activity in the prediction of recurrent disease in low and intermediate 21-gene RS breast cancer. There was no difference in ER, AR and MAPK pathway activity. PIK3CA alterations were the most common driver mutations, but no difference was found between the groups (p=0.46) and no association with PI3K pathway activity (p=0.86). Higher Ki67 gene expression was associated with recurrences (p=0.042) CONCLUSION: Increased PI3K pathway activity, independent of PIK3CA mutations, may play a role in the recurrence of early-stage breast cancer with low and intermediate 21-gene RS. Pathway analysis can help to identify high-risk patients in this setting.

The Age-Male-Albumin-Bilirubin-Platelets (aMAP) Risk Score Predicts Liver Metastasis Following Surgery for Breast Cancer in Chinese Population: A Retrospective Study

Objective

The current study is conducted to investigate the potential prognostic value of the age-male-albumin-bilirubin-platelets (aMAP) score in breast cancer patients with liver metastasis after surgery.

Methods

This is a retrospective study of 178 breast cancer patients who developed liver metastasis after surgery. These patients were treated and followed up from 2000 to 2018 at our hospital. The aMAP risk score was estimated in accordance with the following formula: . The optimal cutoff value of the aMAP was evaluated via X-tile. Kaplan-Meier, Log-rank and Cox proportional hazards regression models were applied to determine the clinical influence of the aMAP score on the survival outcomes. The nomogram models were established by multivariate analyses. The calibration curves and decision curve analysis were applied to evaluate the estimated performance of the nomogram models.

Results

A total of 178 breast cancer patients were divided into low aMAP score group (<47.6) and high aMAP score group (≥47.6) via X-tile plots. The aMAP score was a potential prognostic factor in multivariate analysis. The median disease free survival (p=0.0013) and overall survival (p=0.0003) in low aMAP score group were longer than in high aMAP score group. The nomograms were constructed to predict the DFS with a C-index of 0.722 (95% CI, 0.673-0.771), and the OS with a C-index of 0.708 (95% CI, 0.661-0.755). The aMAP-based nomograms had good predictive performance.

Conclusion

The aMAP score is a potential prognostic factor in breast cancer with liver metastasis after surgery. The aMAP score-based nomograms were conducive to discriminate patients at high risks of liver metastasis and develop adjuvant treatment and prevention strategies.

Which Patients Need Chemotherapy? From Pathological Risk Factors to Gene Signatures and Evaluation of Endocrine Response

Background

Chemotherapy, used either before or after surgery, has significantly improved survival in early breast cancer. Accurate risk assessment is essential to avoid both overtreatment and undertreatment. This review provides an overview of the evolution of chemotherapy as well as risk factors for tailored systemic therapies in early breast cancer - from pathologic risk factors to gene expression signatures to endocrine response assessment.

Summary

Chemotherapy has improved dramatically in recent decades from its beginnings with conventionally dosed cyclophosphamide plus methotexate plus 5-fluorouracil to dose-dense anthracycline- and taxane-containing regimens. Similarly, risk assessment has evolved starting from traditional pathologic risk factors such as tumor size, axillary nodal status, and grading. In recent decades, gene expression signatures have improved prognostic accuracy with a high level of evidence. In turn, these signatures can be further improved by incorporating the aforementioned pathologic factors. As an important step away from this static assessment, dynamic assessment of proliferation factor Ki-67 after short-term preoperative endocrine treatment has gained interest to improve risk assessment in early hormone receptor-positive breast cancer.

Key Message

This review highlights advances in chemotherapy and risk assessment in early breast cancer, from pathologic risk factors for recurrence to gene expression signatures and endocrine response assessment. These developments are leading to better risk stratification and thus better adaptation of therapies.

Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

PAM50 gene expression subtypes represent a cornerstone in the molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor's underlying clinical subgroup defined by ER, PR, and HER2 status. To do this we used a population-representative and clinically annotated early-stage breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest-centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we demonstrate the tight connection between a tumor's nearest and second-nearest PAM50 centroid. Additionally, we show that the second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node-negative disease. We also note that ERBB2 expression has little impact on PAM50 classification in HER2-positive disease regardless of ER status and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum with prognostic implications.

SEOM-GEICAM-SOLTI clinical guidelines for early-stage breast cancer (2022)

Breast cancer is the leading cause of cancer in women in Spain and its annual incidence is rapidly increasing. Thanks to the screening programs in place, nearly 90% of breast cancer cases are detected in early and potentially curable stages, despite the COVID-19 pandemic possibly having impacted these numbers (not yet quantified). In recent years, locoregional and systemic therapies are increasingly being directed by new diagnostic tools that have improved the balance between toxicity and clinical benefit. New therapeutic strategies, such as immunotherapy, targeted drugs, and antibody-drug conjugates have also improved outcomes in some patient subgroups. This clinical practice guideline is based on a systematic review of relevant studies and on the consensus of experts from GEICAM, SOLTI, and SEOM.

The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience

BACKGROUND

Breast cancer has been categorized into molecular subtypes using immunohistochemical staining (IHC) and fluorescence in situ hybridization (FISH) since the early 2000s. However, recent research suggests that gene expression testing, specifically Prosigna® Prediction Analysis of Microarray 50 (PAM50), provides more accurate classification methods. In this retrospective study, we compared the results of IHC/FISH and PAM50 testing. We also examined the impact of various PAM50 parameters on overall survival (OS) and progression-free survival (PFS).

RESULTS

We analyzed 42 unilateral breast cancer samples, with 18 classified as luminal A, 10 as luminal B, 8 as Human epidermal growth factor receptor 2 (HER2)-positive, and 6 as basal-like using PAM50. Interestingly, 17 out of the 42 samples (40.47%) showed discordant results between histopathological assessment and the PAM50 classifier. While routine IHC/FISH resulted in classification differences for a quarter to a third of samples within each subtype, all basal-like tumors were misclassified. Hormone receptor-positive tumors (hazard rate: 8.7803; p = 0.0085) and patients who had higher 10-year recurrence risk scores (hazard rate: 1.0539; p = 0.0201) had shorter OS and PFS.

CONCLUSIONS

Our study supports the existing understanding of molecular subtypes in breast cancer and emphasizes the overlap between clinical characteristics and molecular subtyping. These findings underscore the value of gene expression profiling, such as PAM50, in improving treatment decisions for breast cancer patients.

Chromatin Remodeling Enzyme Cluster Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Breast Cancer

The treatment provided for breast cancer depends on the expression of hormone receptors, human epidermal growth factor receptor-2 (HER2), and cancer staging. Surgical intervention, along with chemotherapy or radiation therapy, is the mainstay of treatment. Currently, precision medicine has led to personalized treatment using reliable biomarkers for the heterogeneity of breast cancer. Recent studies have shown that epigenetic modifications contribute to tumorigenesis through alterations in the expression of tumor suppressor genes. Our aim was to investigate the role of epigenetic modifications in genes involved in breast cancer. A total of 486 patients from The Cancer Genome Atlas Pan-cancer BRCA project were enrolled in our study. Hierarchical agglomerative clustering analysis further divided the 31 candidate genes into 2 clusters according to the optimal number. Kaplan–Meier plots showed worse progression-free survival (PFS) in the high-risk group of gene cluster 1 (GC1). In addition, the high-risk group showed worse PFS in GC1 with lymph node invasion, which also presented a trend of better PFS when chemotherapy was combined with radiotherapy than when chemotherapy was administered alone. In conclusion, we developed a novel panel using hierarchical clustering that high-risk groups of GC1 may be promising predictive biomarkers in the clinical treatment of patients with breast cancer.

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.

Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer

Molecular diagnostic tests help clinicians understand the underlying biological mechanisms of their patients' breast cancer (BC) and facilitate clinical management. Several tissue-based mRNA tests are used routinely in clinical practice, particularly for assessing the BC recurrence risk, which can guide treatment decisions. However, blood-based mRNA assays have only recently started to emerge. This review explores the commercially available blood mRNA diagnostic assays for BC. These tests enable differentiation of BC from non-BC subjects (Syantra DX, BCtect), detection of small tumours <10 mm (early BC detection) (Syantra DX), detection of different cancers (including BC) from a single blood sample (multi-cancer blood test Aristotle), detection of BC in premenopausal and postmenopausal women and those with high breast density (Syantra DX), and improvement of diagnostic outcomes of DNA testing (variant interpretation) (+RNAinsight). The review also evaluates ongoing transcriptomic research on exciting possibilities for future assays, including blood transcriptome analyses aimed at differentiating lymph node positive and negative BC, distinguishing BC and benign breast disease, detecting ductal carcinoma in situ, and improving early detection further (expression changes can be detected in blood up to eight years before diagnosing BC using conventional approaches, while future metastatic and non-metastatic BC can be distinguished two years before BC diagnosis).

Prognostic factors and adjuvant systemic therapy for patients with HER2-positive T1N0 breast cancer: evidence from a real-world study with long-term follow-up

PURPOSE

The optimal adjuvant systemic treatment and potential prognostic factors for patients with T1N0 HER2-positive breast cancer are still unclear. We conducted a real-world study in this relatively low-risk population to identify the clinical-pathological factors of potential prognostic value and to compare the efficacy of different adjuvant strategies.

METHODS

We included patients with HER2-positive T1N0 breast cancer of infiltrating ductal carcinoma (IDC) histology treated at the Cancer Hospital, Chinese Academy of Medical Sciences from April 2010 to April 2017. We performed Cox multivariate analysis to identify the potential prognostic factors for invasive disease-free survival (IDFS). We also compared survival outcomes of (1) patients treated with adjuvant chemotherapy alone, or chemotherapy plus trastuzumab, or observation; (2) patients receiving adjuvant anthracycline-based and non-anthracycline regimens, both combined with trastuzumab. Inverse probability of treatment weighting (IPTW) propensity score was used to reduce selection bias.

RESULTS

Overall, 692 consecutive patients were included, with a median follow-up of 78.0 months for IDFS. Age ≤ 40, T1c, ER + PR + , and adjuvant trastuzumab were identified as independent prognostic factors. For adjuvant treatment, compared with observation and chemotherapy alone, chemotherapy plus trastuzumab could significantly benefit patients (HR = 2.70, P = 0.034; HR = 3.95, P < 0.001). Meanwhile, compared with observation, chemotherapy alone did not significantly benefit patients (HR = 1.37, P = 0.424). For the comparison of anthracycline-based versus non-anthracycline regimens when combined with trastuzumab, patients in both groups had similar IDFS (HR = 1.74, P = 0.242).

CONCLUSIONS

HER2-positive T1N0 IDC patients could benefit from adjuvant chemotherapy plus trastuzumab. Age ≤ 40, T1c, ER + PR + , and adjuvant trastuzumab are independent prognostic factors for this population.

Neoadjuvant endocrine therapy for luminal breast tumors: State of the art, challenges and future perspectives

Neoadjuvant endocrine treatment (NET) associates to satisfactory rates of breast conservative surgery and conversions from inoperable to operable hormone receptor-positive (HR+)/HER2-negative breast cancer (BC), with less toxicities than neoadjuvant chemotherapy (NACT) and similar outcomes. Hence, it has been proposed as a logical alternative to NACT in patients with HR+/HER2- BC candidate to a neoadjuvant approach. Nevertheless, potential barriers to the widespread use of NET include the heterogeneous nature of patient response coupled with the long duration needed to achieve a clinical response. However, interest in NET has significantly increased in the last decade, owing to more in-depth investigation of several biomarkers for a more adequate patient selection and on-treatment benefit monitoring, such as PEPI score, Ki67 and genomic assays. This review is intended to describe the state-of-the-art regarding NET, its future perspectives and potential integration with molecular biomarkers for the optimal selection of patients, regimen and duration of (neo)adjuvant treatments.

Esr1 but Not CYP19A1 Overexpression in Mammary Epithelial Cells during Reproductive Senescence Induces Pregnancy-Like Proliferative Mammary Disease Responsive to Anti-Hormonals

Molecular-level analyses of breast carcinogenesis benefit from vivo disease models. Estrogen receptor 1 (Esr1) and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) overexpression targeted to mammary epithelial cells in genetically engineered mouse models induces largely similar rates of proliferative mammary disease in prereproductive senescent mice. Herein, with natural reproductive senescence, Esr1 overexpression compared with CYP19A1 overexpression resulted in significantly higher rates of preneoplasia and cancer. Before reproductive senescence, Esr1, but not CYP19A1, overexpressing mice are tamoxifen resistant. However, during reproductive senescence, Esr1 mice exhibited responsiveness. Both Esr1 and CYP19A1 are responsive to letrozole before and after reproductive senescence. Gene Set Enrichment Analyses of RNA-sequencing data sets showed that higher disease rates in Esr1 mice were accompanied by significantly higher expression of cell proliferation genes, including members of prognostic platforms for women with early-stage hormone receptor-positive disease. Tamoxifen and letrozole exposure induced down-regulation of these genes and resolved differences between the two models. Both Esr1 and CYP19A1 overexpression induced abnormal developmental patterns of pregnancy-like gene expression. This resolved with progression through reproductive senescence in CYP19A1 mice, but was more persistent in Esr1 mice, resolving only with tamoxifen and letrozole exposure. In summary, genetically engineered mouse models of Esr1 and CYP19A1 overexpression revealed a diversion of disease processes resulting from the two distinct molecular pathophysiological mammary gland-targeted intrusions into estrogen signaling during reproductive senescence.

A Novel Prognostic Prediction Model Based on Pyroptosis-Related Clusters for Breast Cancer

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that pyroptosis is inextricably involved in the development of cancer and may activate tumor-specific immunity and/or enhance the effectiveness of existing therapies. We constructed a novel prognostic prediction model for BC, based on pyroptosis-related clusters, according to RNA-seq and clinical data downloaded from TCGA. The proportions of tumor-infiltrating immune cells differed significantly in the two pyroptosis clusters, which were determined according to 38 pyroptosis-related genes, and the immune-related pathways were activated according to GO and KEGG enrichment analysis. A 56-gene signature, constructed using univariate and multivariate Cox regression, was significantly associated with progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) of patients with BC. Cox analysis revealed that the signature was significantly associated with the PFI and DSS of patients with BC. The signature could efficiently distinguish high- and low-risk patients and exhibited high sensitivity and specificity when predicting the prognosis of patients using KM and ROC analysis. Combined with clinical risk, patients in both the gene and clinical low-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of the clinical event than those who did not. This study presents a novel 56-gene prognostic signature significantly associated with PFI, DSS, and OS in patients with BC, which, combined with the TNM stage, might be a potential therapeutic strategy for individualized clinical decision-making.

Comparing Genetic Risk and Clinical Risk Classification in Luminal-like Breast Cancer Patients Using a 23-Gene Classifier

Background: A 23-gene classifier has been developed based on gene expression profiles of Taiwanese luminal-like breast cancer. We aim to stratify risk of relapse and identify patients who may benefit from adjuvant chemotherapy based on genetic model among distinct clinical risk groups. Methods: There were 248 luminal (hormone receptor-positive and human epidermal growth factor receptor II-negative) breast cancer patients with 23-gene classifier results. Using the modified Adjuvant! Online definition, clinical high/low-risk groups were tabulated with the genetic model. The primary endpoint was a recurrence-free interval (RFI) at 5 years. Results: There was a significant difference between the high/low-risk groups defined by the 23-gene classifier for the 5-year prognosis of recurrence (16 recurrences in high-risk and 3 recurrences in low-risk; log-rank test: p < 0.0001). Among the clinically high-risk group, the 5-year RFI of high risk defined by the 23-gene classifier was significantly higher than that of the low-risk group (15 recurrences in high-risk and 2 recurrences in low-risk; log-rank test: p < 0.0001). Conclusion: This study showed that 23-gene classifier can be used to stratify clinically high-risk patients into distinct survival patterns based on genomic risks and displays the potentiality to guide adjuvant chemotherapy. The 23-gene classifier can provide a better estimation of breast cancer prognosis which can help physicians make a better treatment decision.

Breast Cancer Dataset, Classification and Detection Using Deep Learning

Incorporating scientific research into clinical practice via clinical informatics, which includes genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment. Computational pathology is a growing subspecialty with the potential to integrate whole slide images, multi-omics data, and health informatics. Pathology and laboratory medicine are critical to diagnosing cancer. This work will review existing computational and digital pathology methods for breast cancer diagnosis with a special focus on deep learning. The paper starts by reviewing public datasets related to breast cancer diagnosis. Additionally, existing deep learning methods for breast cancer diagnosis are reviewed. The publicly available code repositories are introduced as well. The paper is closed by highlighting challenges and future works for deep learning-based diagnosis.

Mammography radiomics features at diagnosis and progression-free survival among patients with breast cancer

BACKGROUND

The associations between mammographic radiomics and breast cancer clinical endpoints are unclear. We aimed to identify mammographic radiomics features associated with breast cancer prognosis.

METHODS

Nested from a large breast cancer cohort in our institution, we conducted an extreme case-control study consisting of 207 cases with any invasive disease-free survival (iDFS) endpoint <5 years and 207 molecular subtype-matched controls with >5-year iDFS. A total of 632 radiomics features in craniocaudal (CC) and mediolateral oblique (MLO) views were extracted from pre-treatment mammography. Logistic regression was used to identify iDFS-associated features with multiple testing corrections (Benjamini-Hochberg method). In a subsample with RNA-seq data (n = 96), gene set enrichment analysis was employed to identify pathways associated with lead features.

RESULTS

We identified 15 iDFS-associated features from CC-view yet none from MLO-view. S(1,-1)SumAverg and WavEnLL_s-6 were the lead ones and associated with favourable (OR 0.64, 95% CI 0.42-0.87, P = 0.01) and poor iDFS (OR 1.53, 95% CI 1.31-1.76, P = 0.01), respectively. Both features were associated with eight pathways (primarily involving cell cycle regulation) in tumour but not adjacent normal tissues.

CONCLUSION

Our findings suggest mammographic radiomics features are associated with breast cancer iDFS, potentially through pathways involving cell cycle regulation.

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

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

Clinical Utility of Genomic Assay in Node-Positive Early-Stage Breast Cancer

Breast cancer (BC) is the most common malignancy among women in Canada. Adjuvant treatment in early BC can reduce the risk of BC recurrence. Historically, the decision for adjuvant chemotherapy for early BC was made only based on clinical and tumour characteristics. In recent years, there has been an effort toward developing genomic assays as a predictive and prognostic tool to improve precision in estimating disease recurrence, sensitivity to systemic treatment and ultimately with clinical utility for guidance regarding adjuvant systemic treatment(s). There are various commercial genomic tests available for early-stage ER+/HER-2 negative BC. This paper will review the Oncotype DX 21-gene Recurrence Score (RS), MammaPrint, EndoPredict, Prosigna®, and Breast Cancer Index (BCI) genomic assays. We will also focus on these genomic assays’ clinical application and utility in node-positive early-stage BC based on the most recent evidence and guidance recommendations.

The Tumor-Specific Expression of L1 Retrotransposons Independently Correlates with Time to Relapse in Hormone-Negative Breast Cancer Patients

BACKGROUND

Long-Interspersed Nuclear Element (L1) retrotransposons are silenced in healthy tissues but unrepressed in cancer. Even if L1 reactivation has been associated with reduced overall survival in breast cancer (BC) patients, a comprehensive correlation with clinicopathological features is still missing.

METHODS

Using quantitative, reverse-transcription PCR, we assessed L1 mRNA expression in 12 BC cells, 210 BC patients and in 47 normal mammary tissues. L1 expression was then correlated with molecular and clinicopathological data.

RESULTS

We identified a tumor-exclusive expression of L1s, absent in normal mammary cells and tissues. A positive correlation between L1 expression and tumor dedifferentiation, lymph-node involvement and increased immune infiltration was detected. Molecular subtyping highlighted an enrichment of L1s in basal-like cells and cancers. By exploring disease-free survival, we identified L1 overexpression as an independent biomarker for patients with a high risk of recurrence in hormone-receptor-negative BCs.

CONCLUSIONS

Overall, L1 reactivation identified BCs with aggressive features and patients with a worse clinical fate.

A look at current and potential treatment approaches for hormone receptor-positive, HER2-negative early breast cancer

The heterogeneity of hormone receptor (HR)-positive, HER2-negative early breast cancers reinforces the importance of individualized, risk-adapted treatment approaches. Numerous factors contribute to the risk for recurrence, including clinical tumor features, individual biomarkers, and genomic risk. Current standard approaches for patients with HR-positive, HER2-negative, early stage disease focus on endocrine therapy and chemotherapy. The specific treatment regimen and duration of adjuvant therapy should be selected based on accurate risk assessment, tolerability of available therapies, and consideration for patient preferences. For patients with high-risk features, such as highly proliferative tumors, large tumor size, and significant nodal involvement, the risk for recurrence remains clinically significant despite appropriate adjuvant treatment with current standards of care. This has driven investigation into novel treatment approaches, including the addition of cyclin-dependent kinase 4 and 6 inhibitors to adjuvant endocrine therapy. Cyclin-dependent kinase 4 and 6 inhibition has demonstrated significant efficacy in patients with high-risk, HR-positive, HER2-negative, nonmetastatic breast cancer and now offers a new strategy to greatly improve outcomes in this difficult to treat patient population.; LAY SUMMARY: Hormone receptor (HR)-positive, HER2-negative early breast cancers are highly diverse and need to be managed differently for individual patients. The use of adjuvant endocrine therapy and chemotherapy should be driven by a patient's risk for recurrence, preferences, and risk for side effects. Patients with high-risk tumors have a persistently elevated risk for recurrence despite current standards of care. Emerging cyclin-dependent kinase 4 and 6 inhibitors are highly effective when added to endocrine therapy in high-risk, HR-positive early breast cancer and have the potential to improve patient outcomes in this difficult to treat patient population.

Prognostic significance of different molecular typing methods and immune status based on RNA sequencing in HR-positive and HER2-negative early-stage breast cancer

BACKGROUND

This study was conducted to evaluate the prognostic significance of different molecular typing methods and immune status based on RNA sequencing (RNA-seq) in hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative (HR + /HER2-) early-stage breast cancer and develop a modified immunohistochemistry (IHC)-based surrogate for intrinsic subtype analysis.

METHODS

The gene expression profiles of samples from 87 HR + /HER2- early-stage breast cancer patients were evaluated using the RNA-seq of Oncotype Dx recurrence score (RS), PAM50 risk of recurrence (ROR), and immune score. Intrinsic tumor subtypes were determined using both PAM50- and IHC-based detection of estrogen receptor, progesterone receptor, Ki-67, epidermal growth factor receptor, and cytokeratins 14 and 5/6. Prognostic variables were analyzed through Cox regression analysis of disease-free survival (DFS) and distant metastasis-free survival (DMFS).

RESULTS

Survival analysis showed that ROR better predicted recurrence and distant metastasis compared to RS (for DFS: ROR, P = 0.000; RS, P = 0.027; for DMFS, ROR, P = 0.047; RS, P = 0.621). Patients with HR + /HER2- early-stage breast cancer was classified into the luminal A, luminal B, HER2-enriched, and basal-like subtypes by PAM50. Basal-like subgroups showed the shortest DFS and DMFS. A modified IHC-based surrogate for intrinsic subtype analysis improved the concordance with PAM50 from 66.7% to 73.6%, particularly for basal-like subtype identification. High level of TILs and high expression of immune genes predicted poor prognosis. Multi-factor Cox analysis showed that IHC-based basal-like markers were the only independent factors affecting DMFS.

CONCLUSIONS

Prognosis is better evaluated by PAM50 ROR in early-stage HR + /HER2- breast cancer and significantly differs among intrinsic subtypes. The modified IHC-based subtype can improve the basal-like subtype identification of PAM50. High immunity status and IHC-based basal-like markers are negative prognostic factors.

Association between tumor 18F-fluorodeoxyglucose metabolism and survival in women with estrogen receptor-positive, HER2-negative breast cancer

We examined whether ¹⁸F-fluorodeoxyglucose metabolism is associated with distant relapse-free survival (DRFS) and overall survival (OS) in women with estrogen receptor (ER)-positive, HER2-negative breast cancer. This was a cohort study examining the risk factors for survival that had occurred at the start of the study. A cohort from Asan Medical Center, Korea, recruited between November 2007 and December 2014, was included. Patients received anthracycline-based neoadjuvant chemotherapy. The maximum standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) was measured. The analysis included 466 women. The median (interquartile range) follow-up period without distant metastasis or death was 6.2 (5.3-7.6) years. Multivariable analysis of hazard ratio (95% confidence interval [CI]) showed that the middle and high tertiles of SUV were prognostic for DRFS (2.93, 95% CI 1.62-5.30; P < 0.001) and OS (4.87, 95% CI 1.94-12.26; P < 0.001). The 8-year DRFS rates were 90.7% (95% CI 85.5-96.1%) for those in the low tertile of maximum SUV vs. 73.7% (95% CI 68.0-79.8%) for those in the middle and high tertiles of maximum SUV. ¹⁸F-fluorodeoxyglucose PET/CT may assess the risk of distant metastasis and death in ER-positive, HER2-negative patients.

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.

‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’

In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.

Federated Random Forests can improve local performance of predictive models for various healthcare applications

MOTIVATION

Limited data access has hindered the field of precision medicine from exploring its full potential, e.g. concerning machine learning and privacy and data protection rules.Our study evaluates the efficacy of federated Random Forests (FRF) models, focusing particularly on the heterogeneity within and between datasets. We addressed three common challenges: (i) number of parties, (ii) sizes of datasets and (iii) imbalanced phenotypes, evaluated on five biomedical datasets.

RESULTS

The FRF outperformed the average local models and performed comparably to the data-centralized models trained on the entire data. With an increasing number of models and decreasing dataset size, the performance of local models decreases drastically. The FRF, however, do not decrease significantly. When combining datasets of different sizes, the FRF vastly improve compared to the average local models. We demonstrate that the FRF remain more robust and outperform the local models by analyzing different class-imbalances.Our results support that FRF overcome boundaries of clinical research and enables collaborations across institutes without violating privacy or legal regulations. Clinicians benefit from a vast collection of unbiased data aggregated from different geographic locations, demographics and other varying factors. They can build more generalizable models to make better clinical decisions, which will have relevance, especially for patients in rural areas and rare or geographically uncommon diseases, enabling personalized treatment. In combination with secure multi-party computation, federated learning has the power to revolutionize clinical practice by increasing the accuracy and robustness of healthcare AI and thus paving the way for precision medicine.

AVAILABILITY AND IMPLEMENTATION

The implementation of the federated random forests can be found at https://featurecloud.ai/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Personalizing Adjuvant Endocrine Therapy for Early-Stage Hormone Receptor-Positive Breast Cancer

Endocrine therapy has undergone major changes in the past few years, and is no longer a "one- size- fits- all" prescription. This article discussed some of the new developments and directions.

Immunohistochemical Evaluation of BAP1 Expression in Breast Cancer with Known BRCA1 and BRCA2 Mutations and Comparison with Histopathological Features

Introduction. BRCA-mutated breast cancers have specific pathological characteristics. BAP1 is a tumor suppressor gene that is important in many cancers with different pathways. The relationship between BRCA1 mutation and BAP1 immunohistochemical staining is still unclear. Our aim is to determine whether BAP1 immunohistochemical expression indicates BRCA mutation status in breast carcinomas with specific pathological characteristics. In addition, we aim to determine the histopathological characteristics of tumors according to BRCA mutations. Methods. Histomorphology, molecular subtypes and BAP1 immunohistochemical expression patterns of the BRCA1/BRCA2 mutated and non-mutated tumors were evaluated. The BAP1 immunohistochemical stain was applied to nine tumor tissues with the BRCA1 mutation, six tumor tissues with the BRCA2 mutation, and 16 tumor tissues without any BRCA mutation. Pearson's chi square test and the Fisher Freeman Halton test were used to analyze the associations between the datas. The statistical significance was considered as P value of <.05. Results. Immunohistochemical BAP1 loss was not detected in any mutated or non-mutated tumor group. BRCA1 mutated tumors had the statistically highest histopathological grade (P = .04) and BRCA1/2 mutated tumors had significant immunohistochemical triple negative expression pattern (P = .01). Conclusions. Intrinsic and histopathological characteristics may vary between BRCA1 mutated and non-BRCA1 mutated tumors. Also, BAP1 loss was not detected in BRCA mutated breast tumors because of several effects of BAP1 that are non-related with BRCA in the cell cycle.

Therapeutic Targeting of Minimal Residual Disease to Prevent Late Recurrence in Hormone-Receptor Positive Breast Cancer: Challenges and New Approaches

While the majority of breast cancers are diagnosed at a curable stage, approximately 20% of women will experience recurrence at a distant site during their lifetime. These metastatic recurrences are incurable with current therapeutic approaches. Over the past decade, the biologic mechanisms underlying these recurrences have been elucidated, establishing the existence of minimal residual disease in the form of circulating micrometastases and dormant disease, primarily in the bone marrow. Numerous technologies are now available to detect minimal residual disease (MRD) after breast cancer treatment, but it is yet unknown how to best target and eradicate these cells, and whether clearance of detectable disease prior to the formation of overt metastases can prevent ultimate progression and death. Clinical trials to test this hypothesis are challenging due to the rare nature of MRD in the blood and bone marrow, resulting in the need to screen a large number of survivors to identify those for study. Use of prognostic molecular tools may be able to direct screening to those patients most likely to harbor MRD, but the relationship between these predictors and MRD detection is as yet undefined. Further challenges include the lack of a definitive assay for MRD with established clinical utility, difficulty in selecting potential interventions due to limitations in understanding the biology of MRD, and the emotional impact of detecting MRD in patients who have completed definitive treatment and have no evidence of overt metastatic disease. This review provides a roadmap for tackling these challenges in the design and implementation of interventional clinical trials aimed at eliminating MRD and ultimately preventing metastatic disease to improve survival from this disease, with a specific focus on late recurrences in ER+ breast cancer.

Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer

BACKGROUND

Immune checkpoint inhibitors prolong the survival of non-small cell lung cancer (NSCLC) patients. Although it has been acknowledged that there is some correlation between the efficacy of anti-programmed cell death-1 (PD-1) antibody therapy and immunohistochemical analysis, this technique is not yet considered foolproof for predicting a favorable outcome of PD-1 antibody therapy. We aimed to predict the efficacy of nivolumab based on a comprehensive analysis of RNA expression at the gene level in advanced NSCLC.

METHODS

This was a retrospective study on patients with NSCLC who were administered nivolumab at the Kansai Medical University Hospital. To identify genes associated with response to anti-PD-1 antibodies, we grouped patients into responders (complete and partial response) and non-responders (stable and progressive disease) to nivolumab therapy. Significant genes were then identified for these groups using Welch's t-test.

RESULTS

Among 42 analyzed cases (20 adenocarcinomas and 22 squamous cell carcinomas), enhanced expression of MAGE-A4, BBC3, and OTOA genes was observed in responders with adenocarcinoma, and enhanced expression of DAB2, HLA-DPB,1 and CDH2 genes was observed in responders with squamous cell carcinoma.

CONCLUSIONS

This study predicted the efficacy of nivolumab based on a comprehensive analysis of mRNA expression at the gene level in advanced NSCLC. We also revealed different gene expression patterns as predictors of the effectiveness of anti PD-1 antibody therapy in adenocarcinoma and squamous cell carcinoma.

Transferring MINDACT to Daily Routine: Implementation of the 70-Gene Signature in Luminal Early Breast Cancer - Results from a Prospective Registry of the Austrian Group Medical Tumor Therapy (AGMT)

Background

For hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer (EBC), adjuvant chemotherapy (ACT) is recommended in the case of high-risk features only. The MINDACT trial showed that patients with high clinical risk (CR) but low genomic risk (GR) defined by the 70-gene signature (MammaPrint®; 70-GS) did not benefit from ACT. In this registry, we investigated the frequency and feasibility of 70-GS and concurrent 80-gene subtyping (BluePrint®) use in HR-positive, HER2-negative EBC. Furthermore, we recorded the frequency of ACT recommendation and the adherence to it when the "MINDACT strategy" was used.

Methods

This prospective registry included patients from 2 Austrian cancer centers. Similar to MINDACT, a modified version of Adjuvant!Online was used to determine CR, and 70-GC was used to determine GR in high-CR patients. ACT was recommended to patients with high CR and high GR.

Results

Of 224 enrolled patients, 76 (33.9%) had high CR and 67 (88.2%) received genomic testing. Of those, 43 (64.2%) were classified as low and 24 (35.8%) as high GR, respectively. All 24 patients with high CR and GR (10.7% of all patients) received the recommendation for ACT, but ACT was started in only 15 patients (62.5%). The median time from surgery to the start of ACT was 45 days (range 32-68), and the median time from test decision to the test result was 15 days (range 9-56).

Conclusion

We showed that the results of the MINDACT trial are reproducible in an Austrian population. Incorporating 70-GS into the daily clinical routine is feasible and mostly accepted by physicians for the guidance of treatment recommendations.

How we treat HR-positive, HER2-negative early breast cancer

The present goal of therapy for early hormone receptor-positive (HR+)/human EGF receptor 2-negative (HER2-) BC is to optimize disease-free survival (DFS) and overall survival (OS) rates with the currently available therapies while avoiding any relevant long-term sequalae. Local therapies have evolved toward less aggressive techniques (i.e. breast-preserving surgery, sentinel lymph node biopsy and intraoperative radiotherapy), which significantly reduce the long-term sequalae observed with more radical treatments. Endocrine therapy (ET) is still the cornerstone of adjuvant treatment because it significantly reduces BC relapse and mortality. Adjuvant chemotherapy is today recommended only for a particular subset of patients with a high risk of recurrence with ET alone, identified through genomic assays, age and/or disease stage. Bisphosphonates reduce the risk of bone metastasis and produce a slight although statistically significant improvement in survival in postmenopausal women. The CDK 4/6 inhibitor abemaciclib has been recently approved by the US FDA for patients at high risk of relapse.

The Clinical Research and Latest Application of Genomic Assays in Early-Stage Breast Cancer

Breast cancer is a kind of malignant tumor that seriously endangers women's life and health. Once diagnosed, most patients will receive a combination of treatments to achieve a cure. However, breast cancer is a heterogeneous disease. Even with the same clinical stage and pathological features, its response to treatment and postoperative recurrence risk may still be completely different. With the advent of genomic assay, some patients with early-stage breast cancer who originally needed treatment can still achieve long-term disease-free survival without adjuvant chemotherapy, so as to achieve personalized and accurate treatment mode to a certain extent. In this paper, we reviewed the 5 most widely used and studied genomic panel technologies in breast cancer, namely Oncotype DX, MammaPrint, RecurIndex, PAM50, and EndoPredict, according to accessibility and availability. Based on the results of the completed or ongoing clinical studies, we summarized the origin, applicable population, and clinical efficacy of each detection method, and discussed the potential development prospect of detection technology in the future.

Surrogate endpoints for early-stage breast cancer: a review of the state of the art, controversies, and future prospects

Drug approval for early-stage breast cancer (EBC) has been historically granted in the context of registration trials based on adequate outcomes such as disease-free survival and overall survival. Improvements in long-term outcomes have made it more difficult to demonstrate the clinical benefit of a new cancer drug in large, randomized, comparative clinical trials. Therefore, the use of surrogate endpoints rather than traditional measures allows for cancer drug trials to proceed with smaller sample sizes and shorter follow-up periods, which reduces drug development time. Among surrogate endpoints for breast cancer, the increase in pathological complete response (pCR) rates was considered appropriate for accelerated drug approval. The association between pCR and long-term outcomes was strongest in patients with aggressive tumor subtypes, such as triple-negative and human epidermal growth factor receptor 2 (HER2)-positive/hormone receptor-negative breast cancers. Whereas in hormone receptor-positive/HER2-negative EBC, the most accepted surrogate markers for endocrine therapy-based trials include changes in Ki67 and the preoperative endocrine prognostic index. Beyond the classic endpoints, further prognostic tools are required to provide EBC patients with individualized and effective therapies, and the neoadjuvant setting provides an excellent platform for drug development and biomarker discovery. Nowadays, the availability of multigene signatures is offering a standardized quantitative and reproducible tool to potentiate the efficacy of standard treatment for high-risk patients and develop de-escalated treatments for patients at lower risk of relapse. In this article, we first evaluate the surrogacies used for long-term outcomes and the underlying evidence supporting the use of each surrogate endpoint for the accelerated or regular drug approval process in EBC. Next, we provide an overview of the most recent studies and innovative strategies in a (neo)adjuvant setting as a platform to accelerate new drug approval. Finally, we highlight some clinical trials aimed at tailoring systemic treatment of EBC using prognosis-related factors or early biomarkers of drug sensitivity or resistance.

How to Perform Repeat Sentinel Node Biopsy Safely After a Previous Mastectomy: Technical Features and Oncologic Outcomes

BACKGROUND

The latest National Comprehensive Cancer Network Breast Cancer Guidelines still discourage repeat sentinel node biopsy (SNB) after mastectomy, and the largest multicentric study available reports only 35 cases in the absence of previous axillary dissection (AD).

METHODS

From January 2003 to November 2018, 89 patients of the European Institute of Oncology with local recurrence of breast cancer after mastectomy, free of distant metastases, with a clinically negative axilla and a negative axillary ultrasound, in absence of AD, underwent lymphatic mapping before wide local excision.

RESULTS

During surgery, SNB was successful for 99% of the patients, with 14% being metastatic. Additional metastatic nodes removed by AD after a positive sentinel node occurred in 82% of cases. After a medium follow-up period of 3.7 years, the overall survival rate was 96.7%, and the disease-free survival rate was 84.4%. No axillary relapse after AD was recorded. One patient who refused human epidermal growth factor receptor 2 (HER2)-targeted treatment experienced ipsilateral axillary recurrence after a negative repeat SNB. The first axillary level was never directly irradiated because all the patients with positive repeat SNB underwent AD. For invasive luminal-like HER2-negative recurrences, the metastatic sentinel node was significantly associated with the choice to prescribe adjuvant chemotherapy (p = 0.003).

CONCLUSIONS

In specialized centers, repeat axillary SNB for patients with local recurrence after mastectomy in the absence of previous AD can represent a safe option for detection and removal of occult axillary disease that would otherwise not be excised/irradiated to achieve better local control and could possibly influence the choice of adjuvant treatments.

Prognostic Utility of Breast Cancer Index to Stratify Distant Recurrence Risk in Invasive Lobular Carcinoma

PURPOSE

The prognostic utility of Breast Cancer Index (BCI) for risk assessment of overall (0-10 years), early (0-5 years), and late (5-10 years) distant recurrence (DR) in hormone receptor-positive (HR+) invasive lobular carcinoma (ILC) was evaluated.

EXPERIMENTAL DESIGN

BCI gene expression analysis was performed blinded to clinical outcome utilizing tumor specimens from patients with HR+ ILC from a multi-institutional cohort. The primary endpoint was time to DR. Kaplan-Meier analyses of overall, early, and late DR risk were performed, and statistical significance was evaluated by log-rank test and Cox proportional hazards regression. The prognostic contribution of BCI in addition to clinicopathologic factors was evaluated by likelihood ratio analysis.

RESULTS

Analysis of 307 patients (99% ER+, 53% T1, 42% N+, 70% grade II) showed significant differences in DR over 10 years based on BCI risk categories. BCI low- and intermediate-risk patients demonstrated similar DR rates of 7.6% and 8.0%, respectively, compared with 27.0% for BCI high-risk patients. BCI was a significant independent prognostic factor for overall 10-year DR [HR = 4.09; 95% confidence interval (CI), 2.00-8.34; P = 0.0001] as well as for both early (HR = 8.19; 95% CI, 1.85-36.30; P = 0.0042) and late (HR = 3.04; 95% CI, 1.32-7.00; P = 0.0224) DR. In multivariate analysis, BCI remained the only statistically significant prognostic factor for DR (HR = 3.49; 95% CI, 1.28-9.54; P = 0.0150).

CONCLUSIONS

BCI is an independent prognostic factor for ILC and significantly stratified patients for cumulative risk of 10-year, early, and late DR. BCI added prognostic value beyond clinicopathologic characteristics in this distinct subtype of breast cancer.

Predictive Significance of an Optimized Panel for Basal-like Breast Cancer: Results from the Canadian Cancer Trials Group MA.5 and MA.12 Phase III Clinical Trials

PURPOSE

Accurate IHC biomarkers incorporating nestin positivity or inositol polyphosphate-4-phosphate (INPP4B) loss have recently been optimized to identify the basal-like intrinsic breast cancer subtype regardless of estrogen, progesterone, or Her2 status. We examined the predictive capacity of these basal biomarkers in the CCTG MA.5 chemotherapy and MA.12 endocrine therapy trials.

EXPERIMENTAL DESIGN

Formalin-fixed paraffin embedded blocks of primary tumors from patients randomized in the two trials were used to build tissue microarrays. IHC staining for nestin and INPP4B followed published methods and REMARK criteria. A prespecified statistical plan tested the hypothesis that patients with basal breast cancer (nestin⁺ or INPP4B^-) would not benefit from anthracycline substitution in MA.5 or from tamoxifen in MA.12.

RESULTS

Nestin positivity or INPP4B loss was observed in 110/453 (24%) interpretable samples from MA.5 and 47/366 (13%) from MA.12, and was associated with high grade, younger age, estrogen receptor negativity, triple-negative, core basal, and PAM50 basal-like subtypes. In the MA.5 trial, patients assigned as basal experienced lower benefit from anthracycline versus nonanthracycline adjuvant chemotherapy [HR, 1.49; 95% confidence interval (CI), 0.72-3.10] when compared with non-basal (nestin^- and INPP4B⁺) cases where there was a higher benefit from anthracyclines (HR, 0.75; 95% CI, 0.54-1.04; P _interaction = 0.01). In the MA.12 trial, patients assigned as basal did not demonstrate a benefit from adjuvant tamoxifen versus placebo (HR, 0.48; 95% CI, 0.12-1.86; P = 0.29), whereas nonbasal cases displayed significant benefit (HR, 0.66; 95% CI, 0.45-0.98; P = 0.04), although the interaction test was not significant.

CONCLUSIONS

The nestin/INPP4B IHC panel identifies women with basal breast cancers who benefit from nonanthracycline chemotherapy but not endocrine adjuvant treatments.

A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that microRNAs (miRNAs) are inextricably involved in the development of cancer. Here, we constructed a novel model, based on miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 962 patients were included in this study, and the relationships among their clinicopathological features, survival, and miRNA-seq expression levels were analyzed. Hsa-miR-186 and hsa-miR-361 were identified as internal reference miRNAs and used to normalize miRNA expression data. A five-miRNA signature, constructed using univariate and multivariate Cox regression, was significantly associated with disease-specific survival (DSS) of patients with BC. Kaplan–Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the five-miRNA signature. Finally, a nomogram was constructed based on the five-miRNA signature to evaluate its clinical value. Cox regression analysis revealed that a five-miRNA signature was significantly associated with DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high- and low-risk patients. Moreover, ROC analysis showed that the five-miRNA signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in the high-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of mortality than those who did not. A nomogram constructed based on the five-miRNA signature was effective in predicting 5-year DSS. This study presents a novel five-miRNA signature as a reliable prognostic tool to predict DSS and provide theoretical reference significance for individualized clinical decisions for patients with BC.