Many patients with cancer do not benefit from currently approved immune checkpoint inhibitors (ICIs), suggesting that additional immunomodulation of the immunosuppressive tumor microenvironment (TME) is required. MTL-CCAAT enhancer-binding protein alpha (CEBPA) specifically upregulates the expression of the master myeloid transcription factor, CEBPA, relieving myeloid-driven immunosuppression. Here, we report the safety, tolerability, pharmacokinetics, and efficacy of MTL-CEBPA in combination with pembrolizumab in patients with advanced solid tumors that typically show ICI resistance. Multimodal exploratory analyses of paired patient biopsies demonstrate biological changes associated with the combination treatment of MTL-CEBPA and pembrolizumab, including increased infiltration of T cell and antigen-presenting cells supporting conversion from an immune-desert toward a more immune-inflamed TME. Patients with disease stabilization demonstrate reductions in immunosuppressive myeloid cells post treatment. Collectively, these data support a role for MTL-CEBPA in reducing immunosuppression in the TME. This study was registered at ClinicalTrials.gov (NCT04105335).

The Rx for positive node endocrine-responsive breast cancer trial highlighted that premenopausal (PRE) women who underwent chemotherapy exhibited superior survival rates compared to postmenopausal (POST) counterparts, but showed worse survival without chemotherapy. This raises the question whether application of ovarian function suppression (OFS) in PRE women aligns with their cancer biology, treatment response, and outcomes observed in POST women.

Data from the Seoul National University Hospital breast cancer cohort focusing on patients with stage pT1-3, pN0-1, estrogen receptor-positive (ER+), and HER2-negative breast cancer were analyzed. Survival outcomes, including invasive disease-free survival (iDFS) and distant relapse-free survival (DRFS), were compared between PRE women receiving OFS and POST women, with chemotherapy usage as a stratification factor. Propensity score matching was performed.

We analyzed 3483 patients, comprising 2901 POST and 582 PRE women with OFS. In the cohort without chemotherapy, the 10-year iDFS rates were 90.3 % and 88.3 % (hazard ratio [HR], 1.32; p = 0.16), and 10-year DRFS rates were 94.3 % and 96.1 % (HR, 0.78; p = 0.41) for POST and PRE women with OFS, respectively. Among women treated with chemotherapy, 10-year iDFS rates were 83.0 % and 79.5 % (HR, 1.21; p = 0.37), and DRFS rates were 86.7 % and 85.7 % (HR, 1.14; p = 0.58) for POST and PRE women with OFS, respectively. These results remained consistent after PSM.

Oncological outcomes of PRE women receiving OFS were comparable to those of POST women with ER+ and HER2-early breast cancer, irrespective of chemotherapy administration.

RxPONDER showed that in postmenopausal women with early-stage hormone receptor + /HER2- breast cancer (BC) with 1-3 positive axillary lymph nodes (LN) and a recurrence score ≤ 25, the addition of chemotherapy to endocrine therapy did not improve distant recurrence-free survival. We sought to evaluate Oncotype DX recurrence score (ODX RS) distribution in LN negative and LN positive patients aged ≥ 50 years (y) and to determine clinicopathologic factors associated with RS.

ODX RS, demographic, and pathologic information was collected for patients with ER + /HER2- BC with 0 (patients < 50y) or 0-3 positive (patients ≥ 50y) LN treated at our institution between January 2021 and December 2022. Statistical analyses were conducted using Pearson chi-square and two-tailed t tests.

The study cohort included 2378 BC from 2285 women. Among women ≥ 50y, there was no significant difference in RS distribution between pN0, pN1mi, and pN1a patients; with 85.4%, 86.5%, and 81% having a RS ≤ 25, respectively. Among LN + women ≥ 50y, RS > 25 was significantly associated with higher grade (P = .001), lower ER (P = .007), and lower PR (P < .001). Among LN- women ≥ 50y, RS > 25 was significantly associated with higher grade (P < .001), lower ER (P < .001), and lower PR (P < .001).

ODX RS distribution among LN + and LN- women aged ≥ 50y was similar. In this population, RS is significantly associated with tumor grade, ER, and PR, regardless of LN status. In our post-RxPONDER era cohort, over 80% of women aged ≥ 50y with early-stage ER + /HER2- BC with ≤ 3 positive axillary LN would be spared chemotherapy based on RS, regardless of nodal status.

In ER + /HER2- early breast cancer (BC), 21-Gene Recurrence Score (RS) > 25 indicates high-risk of distant-recurrence and predicts benefit from adjuvant chemotherapy (aCT) regardless of tumor-size. However, T1a/b (≤ 1 cm) node-negative (N0) tumors, regarded as of low risk of recurrence, were under-represented in the RS trials. We therefore aimed to investigate the benefit of aCT in patients with T1a/bN0 BC, RS > 25, where clinical and genomic risk indicators are discordant.

This retrospective observational cohort study utilized Israel's national Oncotest database to identify Clalit Health Services (CHS) members, diagnosed with T1a/bN0 HR + /HER2- BC, who underwent RS testing between February 2006, and December 2019. Patients with RS > 25 who received aCT were matched 1:1 by propensity-scoring to similar patients receiving no aCT. Invasive disease-free survival (iDFS) and distant recurrence were the study endpoints. Patient demographic and clinical data were obtained from CHS's centralized database. Kaplan--Meier analysis with log-rank testing was used for comparing outcomes.

During the study period, high-risk RS result (> 25) was identified in 156/9858 patients of the study cohort. aCT was administered to 74 (47.4%) and median follow-up was 121 months. Within the 148 matched-cases, eighteen iDFS-events occurred, nine (12.1%) in each group (χ2 = 0.72, p = 0.39). Four (5.4%) of the aCT treated and three (4.0%) of the untreated patients were diagnosed with distant recurrence (χ2 = 0.22, p = 0.64).

In this study cohort, patients with T1a/bN0 BC, RS > 25 that received aCT, did not have improved outcomes and the 21-Gene RS > 25 was not found to be predictive, possibly due to the low number of events observed.

CDK4/6 inhibitors in combination with endocrine therapy are widely used to treat HR+/HER2- metastatic breast cancer leading to improved progression-free survival (PFS) compared to single agent endocrine therapy. Over 300 patients receiving standard-of-care CDK4/6 inhibitor combination therapy for metastatic disease were enrolled at a single institution. Clinical, pathological, and gene expression data were employed to define determinants for PFS duration. Visceral disease (HR 1.55, p = 0.0013), prior endocrine therapy (HR 2.34, p < 0.001), and the type of endocrine therapy (HR 2.16, p < 0.001) were highly associated with PFS duration. Multiple pre-defined gene expression signatures were employed to determine association with response to CDK4/6 inhibitor-based therapy. Random survival forest was applied to define key gene expression and clinical features associated with PFS and develop a predictive model. The time to progression predicted by this model was related to the median PFS observed in PALOMA-2/3 and PEARL studies. Interrogating genes identified as highly significant across all studies indicated common enrichment of gene networks associated with cell cycle and estrogen receptor signaling. These findings indicate that there are common features from real-world use of CDK4/6 inhibitors that could be used to infer time to progression and better inform treatment.

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in HR+/HER2- breast cancer patients still have limitations. The integration of multidimensional data represents a promising alternative for predicting relapse. In this study, we leverage our multi-omics cohort comprising 579 HR+/HER2- breast cancer patients (200 patients with complete data across 7 modalities) and develop a machine-learning-based model, namely CIMPTGV, which integrates clinical information, immunohistochemistry, metabolomics, pathomics, transcriptomics, genomics, and copy number variations to predict recurrence risk of HR+/HER2- breast cancer. This model achieves concordance indices (C-indices) of 0.871 and 0.869 in the train and test sets, respectively. The risk population predicted by the CIMPTGV model encompasses those identified by single-modality models. Feature analysis reveals that synergistic and complementary effects exist in different modalities. Simultaneously, we develop a simplified model with a mean area under the curve (AUC) of 0.840, presenting a useful approach for clinical applications.

Harmonized global collaborations are crucial to improving outcomes in hormone sensitive operable breast cancer.

Breast cancer (BC) has high rates of incidence and prevalence, causing significant impact in our society. Magnetic resonance imaging (MRI) plays a crucial role in its detection and staging. The Oncotype DX Breast Recurrence Score (ODXRS) test can be used to guide decision making regarding adjuvant chemotherapy (CT) in early-stage luminal BC to allow for more tailored cancer treatment. The aim of this article is to review knowledge regarding MRI biomarkers to date according to the BI-RADS® classification and the use of artificial intelligence (AI) in this imaging technique to establish its correlation with the ODXRS test. The latest studies published on AI and MRI present promising findings, and their standardisation could mark a turning point in breast radiology.

Stratipath Breast is a CE-IVD marked artificial intelligence-based solution for prognostic risk stratification of breast cancer patients into high- and low-risk groups, using haematoxylin and eosin (H&E)-stained histopathology whole slide images (WSIs). In this validation study, we assessed the prognostic performance of Stratipath Breast in two independent breast cancer cohorts.

This retrospective multi-site validation study included 2719 patients with primary breast cancer from two Swedish hospitals. The Stratipath Breast tool was applied to stratify patients based on digitised WSIs of the diagnostic H&E-stained tissue sections from surgically resected tumours. The prognostic performance was evaluated using time-to-event analysis by multivariable Cox Proportional Hazards analysis with progression-free survival (PFS) as the primary endpoint.

In the clinically relevant oestrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative patient subgroup, the estimated hazard ratio (HR) associated with PFS between low- and high-risk groups was 2.76 (95% CI: 1.63-4.66, p-value < 0.001) after adjusting for established risk factors. In the ER+/HER2- Nottingham histological grade (NHG) 2 subgroup, the HR was 2.20 (95% CI: 1.22-3.98, p-value = 0.009) between low- and high-risk groups.

The results indicate an independent prognostic value of Stratipath Breast among all breast cancer patients, as well as in the clinically relevant ER+/HER2- subgroup and the NHG2/ER+/HER2- subgroup. Improved risk stratification of intermediate-risk ER+/HER2- breast cancers provides information relevant for treatment decisions of adjuvant chemotherapy and has the potential to reduce both under- and overtreatment. Image-based risk stratification provides the added benefit of short lead times and substantially lower cost compared to molecular diagnostics and therefore has the potential to reach broader patient groups.

Pure mucinous breast cancer (PMC) is a rare histological type with a favourable prognosis. However, cases with recurrence have been reported and diagnosed in clinical practice. The mechanisms underlying PMC recurrence remain unknown. In this study, we aimed to identify the prognostic factors associated with PMC.

A total of 166 patients diagnosed with PMC were included. We compared the clinicopathological characteristics between patients with and without recurrence. The 21-gene assay was performed in 10 patients with recurrence and 20 TNM stage-matched patients without recurrence. Whole-exon sequencing was performed in 12 PMC primary tumours and four positive lymph nodes (LNs).

Tumour size, lymph node status and TNM staging differed significantly between recurrent group and non-recurrent group. And the 21-gene recurrence scores did not differ significantly between recurrent group and its TNM stage-matched non-recurrent group. The most frequently mutated genes in the primary tumours of regional LN-positive PMCs were ADCY10 (3/6) and SHANK3 (3/6), and they more recurrently harboured gains of 15q23, 17q23.2 and 20p11.21, and loss of 21p11.2. And these alterations were not detected in primary tumours of regional LN-negative PMCs.

TNM stage is an important prognostic factor in PMC. Although we revealed that regional LN-positive PMCs show increased occurrence of duplication variants at 15q23, 17q23.2 and 20p11.21, and deletion variants at 21p11.2. Further investigation, including multi-omics studies, are needed and may provide additional insights into the nature of PMC.

Postoperative radiotherapy in patients with breast cancer with one to three lymph node metastases, particularly within the pT1-2N1M0 cohort with a low clinical risk of local-regional recurrence (LRR), has incited a discourse surrounding personalised treatment strategies. Multigene testing for Recurrence Index (RecurIndex) model capably differentiates patients based on their level of LRR risk. This research aims to validate whether a more aggressive treatment approach can enhance clinical outcomes in N1 patients who possess a clinically low risk of LRR, yet a high RecurIndex-determined risk of LRR. Specifically, this entails postoperative whole breast irradiation combined with regional lymph node irradiation (RNI) following breast-conserving surgery or chest wall irradiation with RNI after mastectomy.

The RIGAIN (RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1-3 node-positive breast cancer) Study is a multicentre, prospective, randomised, open-label, phase III clinical trial that is being conducted in China. In this study, patients with low clinical LRR risk but high RecurIndex-LRR risk are randomly assigned in a 1:1 ratio to the experimental group or the control group. In the experimental group, RNI is performed and the control group omits RNI. Efficacy and safety analyses will be conducted, enrolling a total of 540 patients (270 per group). The primary endpoint is invasive disease-free survival, and secondary endpoints include any first recurrence, LRR-free survival, distant metastasis-free survival, recurrence-free survival, overall survival, disease-free survival, breast cancer-specific mortality and assessment of patient quality of life. The study began in April 2023 and with a follow-up period of 60 months after the last participant completes radiation therapy.

The study was approved by the Ethics Committee of Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University (SYSKY-2022-097-02, V.3.1). It adheres to the Helsinki Declaration and Good Clinical Practice. Research findings will be submitted for publication in peer-reviewed journals.

NCT04069884.

Background: The SOUND study demonstrated that an axillary de-escalation may be sufficient in locoregional and distant disease control in selected early breast cancer (EBC) patients. To establish any preoperative variables that may drive sentinel lymph node biopsy (SLNB) omission, a study named sentinel omission risk factor (SOFT) 1.23 was planned. Methods: A single-center retrospective study from a prospectively maintained database was designed, aiming at underlying preoperative prognostic factors involved in sentinel lymph node (SLN) metastasis (lymph node involvement (LN+) vs. negative lymph node (LN-) group). Secondary outcomes included surgical room occupancy analysis for SLNB in patients fulfilling the SOUND study inclusion criteria. The institutional ethical committee Area Territoriale Lazio 2 approved the study (n° 122/23). Results: Between 1 January 2022 and 30 June 2023, 160 patients were included in the study and 26 (%) were included in the LN+ group. Multifocality, higher cT stage, and larger tumor diameter were reported in the LN+ group (p = 0.020, p = 0.014, and 0.016, respectively). Tumor biology, including estrogen and progesterone receptors, and molecular subtypes showed association with the LN+ group (p < 0.001; p = 0.001; and p = 0.001, respectively). A total of 117 (73.6%) patients were eligible for the SOUND study and the potential operating room time saved was 2696.81 min. Conclusions: De-escalating strategies may rationalize healthcare activities. Multifactorial risk stratification may further refine the selection of patients who could benefit from SLNB omission.

Genomic tests, such as the Oncotype Dx 21-gene and Prosigna risk of recurrence (ROR-P) assay, are commonly used for breast cancer prognostication. Emerging data suggest variability between assays, but this has not been compared in diverse populations.

RNA sequencing was performed on 647 previously untreated stage I-III estrogen receptor-positive/human epidermal growth factor receptor 2-negative tumors in the Carolina Breast Cancer Study, which oversampled Black and younger women (age <50 years at diagnosis), using research versions of two common RNA-based prognostic assays: ROR-PR and the 21-gene recurrence score (RSR). Relative frequency differences and 95% CIs were estimated for associations with race and age, and hazards of 5-year local or distant recurrence were modeled with Cox regression. Proliferation and estrogen module scores from each assay, representing broad activity of genes in those pathways, were examined to guide interpretation of differences between tests.

Among both younger and older individuals, Black women had higher frequency of intermediate and high ROR-PR scores than non-Black women. Race was not significantly associated with RSR in either age group. High (hazard ratio [HR], 4.67 [95% CI, 1.73 to 12.70]) and intermediate (HR, 2.12 [95% CI, 0.98 to 4.62]) ROR-PR scores were associated with greater risk of recurrence, but RSR did not predict recurrence. RSR emphasized estrogen over proliferation modules, whereas ROR-PR emphasized proliferation. Higher proliferation scores were associated with younger age and Black race in both assays. Modifications to the RSR algorithm that increased emphasis on proliferation improved prognostication in this diverse population.

ROR-PR and the 21-gene RSR differentially emphasize estrogen-related and proliferative biology. The emphasis of 21-gene RS on estrogen-related biology and lower endocrine therapy initiation among Black women may contribute to poorer prognostic ability in heterogeneously treated populations.

There is no clear information in the literature about the relationship between the efficacy of CDK 4/6i combined with ET and HR positivity. However, we know that the longest overall survival was in the ER-strong positive/PR intermediate or strong positive groups. Therefore, we aimed to investigate CDK4/6i treatments that create positivity in HR.

Patients with the diagnosis of HR+/HER2- MBC who were treated with CDK 4/6i and HR >10% were retrospectively evaluated. To analyze the role of HR positivity, ER was moderately positive (10-49%) and ER was strongly positive (50-100%); PR was grouped as moderately positive (10-49%) and PR strongly positive (50-100%).

Median follow-up of 150 patients included in the study was 15.2 months (95% CI, 2.1-40.9 months). The highest response in the whole group was obtained in the ER-strong positive/PR moderate or strong positive group, and the ER moderate positive/PR moderate or strong group. This was followed by the ER strong positive/PR negative group, and then the ER moderate positive/PR negative group. Although these advantages were not statistically significant, they were numerically higher (ORR: 83.8% vs. 83.3% vs. 77.4% vs. 62.5%, p=0.488, respectively). The highest survival in the whole group was achieved in the ER strong positive/PR moderate or strongly positive group, followed by the ER moderately positive/PR moderate or strongly positive group, the ER strongly positive/PR negative group followed by the ER moderate positive/PR negative group, respectively(p=0.410). However, these advantages were not statistically significant.

As a result, HR+/HER2- MBC patients receiving CDK 4/6i combined with ET suggest that the percentage of HR positivity may have a predictive and prognostic role.

Given high costs of Oncotype DX (ODX) testing, widely used in recurrence risk assessment for early-stage breast cancer, studies have predicted ODX using quantitative clinicopathologic variables. However, such models have incorporated only small cohorts. Using a cohort of patients from the National Cancer Database (NCDB, n = 53,346), we trained machine learning models to predict low-risk (0-25) or high-risk (26-100) ODX using quantitative estrogen receptor (ER)/progesterone receptor (PR)/Ki-67 status, quantitative ER/PR status alone, and no quantitative features. Models were externally validated on a diverse cohort of 970 patients (median follow-up 55 months) for accuracy in ODX prediction and recurrence. Comparing the area under the receiver operating characteristic curve (AUROC) in a held-out set from NCDB, models incorporating quantitative ER/PR (AUROC 0.78, 95% CI 0.77-0.80) and ER/PR/Ki-67 (AUROC 0.81, 95% CI 0.80-0.83) outperformed the non-quantitative model (AUROC 0.70, 95% CI 0.68-0.72). These results were preserved in the validation cohort, where the ER/PR/Ki-67 model (AUROC 0.87, 95% CI 0.81-0.93, p = 0.009) and the ER/PR model (AUROC 0.86, 95% CI 0.80-0.92, p = 0.031) significantly outperformed the non-quantitative model (AUROC 0.80, 95% CI 0.73-0.87). Using a high-sensitivity rule-out threshold, the non-quantitative, quantitative ER/PR and ER/PR/Ki-67 models identified 35%, 30% and 43% of patients as low-risk in the validation cohort. Of these low-risk patients, fewer than 3% had a recurrence at 5 years. These models may help identify patients who can forgo genomic testing and initiate endocrine therapy alone. An online calculator is provided for further study.

It remains unclear whether patients with HER2-negative, low-estrogen receptor (ER-low)-positive early breast cancer (BC) benefit from Oncotype DX® (ODX) testing.

We conducted a retrospective review of cases referred for ODX testing over a seven-year period from a breast biomarker testing referral center (n = 854). For each case, we recorded the ODX Recurrence Score (RS) along with percentage of ER nuclear positivity and staining intensity on immunohistochemistry. Our criteria for ER-low was defined as ≤10% cells with nuclear positivity and/or weak intensity of staining. Slides from all ER-low cases were reviewed and the reported ODX ER gene scores were recorded. We randomly selected a comparator group of 56 patients with ER > 10% positivity and non-weak staining intensity (ER-high).

We identified 27 cases (3.2%) that met our criteria for ER-low. Of these, 92.6% had a high RS (>25), and 7.4% had a RS of 25. All cases with ≤10% ER nuclear positivity had a high RS. Most ER-low cases (85.2%) had ODX quantitative ER gene scores in the negative range, whereas all (100%) ER-high cases had positive ER gene scores.

ODX does not appear to add significant additional information to inform treatment decisions for most patients with ER-low BC. Incorporating weak ER staining intensity in addition to low percentage of nuclear positivity identifies about twice as many ER-low patients, although with reduced specificity for high RS. Our study supports the contention that most ER-low early BC should be regarded similarly to ER-negative BC.

OncotypeDx is a prognostic and predictive genomic assay used in early-stage hormone receptor-positive, HER2- (HR+/HER2-) breast cancer. It is used to inform adjuvant chemotherapy decisions, but not all eligible women receive testing. We aimed to assess variation in testing by demographics and geography, and to determine whether testing was associated with chemotherapy.

For 1,615 women in the Carolina Breast Cancer Study with HR+/HER2-, Stage I-II tumors, we estimated prevalence differences (PD) and 95% confidence intervals (CI) for receipt of OncotypeDx genomic testing in association with and sociodemographic characteristics. We assessed associations between testing and chemotherapy receipt overall and by race. Finally, we calculated the proportion of eligible women receiving OncotypeDx by county-level rurality, census tract-level socioeconomic status, and Area Health Education Center regions.

38% (N = 609) of potentially eligible women were tested, with lower testing prevalences in Black (31%; PD, -11%; 95% CI, -16%-6%) and low-income women (24%; PD, -20%; 95% CI, -29% to -11%) relative to non-Black and higher income women. Urban participants were less likely to be tested than rural participants, though this association varied by region. Among women with low genomic risk tumors, tested participants were 29% less likely to receive chemotherapy than untested participants (95% CI, -40% to -17%). Racial differences in chemotherapy were restricted to untested women.

Both individual and area-level socioeconomics predict likelihood of OncotypeDx testing.

Variable adoption of OncotypeDx by socioeconomics and across geographic settings may contribute to excess chemotherapy among patients with HR+/HER2- cancers. See related In the Spotlight, p. 635.

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Mining differentially expressed genes of TNBC is helpful to explore new therapeutic targets. This study aimed to investigate diagnostic biomarker genes in TNBC compared to normal tissue. Additionally, we explored the functions and prognostic value of these key genes as well as potential targeted drugs that could affect these genes.

Differential gene expression analysis was conducted using the R software with data from the Gene Expression Omnibus (GEO) database. Then, the identified differentially expressed genes (DEGs) were used to construct a protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The mRNA expression levels of key genes were analyzed using the UALCAN database with data from The Cancer Genome Atlas (TCGA). Enrichment and survival analyses were performed using R software. In addition, potential compounds showing sensitivity to key genes were identified by gene set cancer analysis (GSCA).

Compared with normal tissues, a total of 203 DEGs were upregulated in TNBC. These DEGs participated in various biological processes including nuclear division, microtubule binding, cell cycle, and the p53 signaling pathway. Through the PPI network analysis, ten key genes were identified, among which four genes showed significant correlation with poor progression-free interval (PFI) in patients with TNBC. Moreover, the four survival-related genes were found to act as sensitive therapeutic targets.

The identified four key genes were considered new biomarkers for diagnosis and prognosis and also potential therapeutic targets for TNBC.

We sought to better define estrogen receptor-low-positive (ER-low+) breast cancer biology and determine the utility of the Oncotype DX Breast Recurrence Score® (RS) assay in this population.

Patients with information regarding percentage ER positivity and PAM50 subtype were identified in The Cancer Genome Atlas (TCGA) and subtype distribution was determined. Next, patients with ER-low+ (ER 1-10%), HER2- breast cancer undergoing upfront surgery with known RS result were identified in the National Cancer Database (NCDB) and our institutional Dana-Farber Brigham Cancer Center (DF/BCC) database; RS distribution was examined. Finally, patients with ER-low+, HER2- breast cancer treated at DF/BCC from 2011 to 2020 without prior RS results and in whom tissue was available to perform the assay were identified. RS results, treatment, recurrence and breast cancer-specific survival (BCSS) were determined.

Of 1033 patients in TCGA, ER percentage and PAM50 subtype were available for 342 (33.1%) patients. Forty-six (13.5%) had ER-low+/HER2- tumors, among whom 82.6% were basal and 4.3% were luminal A. Among 3423 patients with ER-low+/HER2- disease in the NCDB, RS results were available for 689 (20.1%) patients; 67% had an RS ≥26. In our institutional database, only two patients with ER-low+/HER2- disease and an RS were identified, both with RS ≥26. Among 37 patients in our institutional cohort without prior RS, 35 (97.4%) had an RS ≥26, determined with testing. After a median follow-up of 40 months (range 3-106), three patients, all treated with chemotherapy, recurred. Three-year BCSS was 97.0% (95% confidence interval 96.9-97.1%).

Most ER-low+/HER2- breast cancers are basal-like, with RS ≥26 suggesting these tumors are similar to triple-negative disease.

Early hormone-positive breast cancers typically have favorable outcomes, yet long-term surveillance is crucial due to the risk of late recurrences. While many studies associate MMP-11 expression with poor prognosis in breast cancer, few focus on early-stage cases. This study explores MMP-11 as an early prognostic marker in hormone-positive breast cancers.

In this retrospective study, 228 women with early hormone-positive invasive ductal carcinoma, treated surgically between 2011 and 2016, were included. MMP-11 expression was measured by immunohistochemistry, and its association with clinical and MRI data was analyzed.

Among the patients (aged 31-89, median 60, with average tumor size of 15.7 mm), MMP-11 staining was observed in half of the cases. This positivity correlated with higher uPA levels and tumor grade but not with nodal status or size. Furthermore, MMP-11 positivity showed specific associations with MRI features. Over a follow-up period of 6.5 years, only 12 oncological events occurred. Disease-free survival was linked to Ki67 and MMP-11.

MMP-11, primarily present in tumor-surrounding stromal cells, correlates with tumor grade and uPA levels. MMP-11 immunohistochemical score demonstrates a suggestive trend in association with disease-free survival, independent of Ki67 and other traditional prognostic factors. This highlights the potential of MMP-11 as a valuable marker in managing early hormone-positive breast cancer.

The prognostic role of the recurrence score (RS) based on the 21-gene expression assay in premenopausal women is not well delineated, and we investigated the association of outcomes and the RS in premenopausal patients who had 21-gene expression assay at Asan Medical Center, Seoul, Korea, between June 2005 and July 2018. Invasive breast cancer-free survival (IBCFS) by STEEP version 2.0 was compared according to the RS and clinical risk factors. A total of 554 patients were included in our study and 116 patients (20.9%) had age <40 years, 238 patients (43.0%) had luminal B subtype (Ki67 ≥ 20%), and 83 patients (15.0%) had RS >25. All patients received adjuvant tamoxifen ± chemotherapy. Overall, patients with RS >25 showed trend toward worse IBCFS from multivariable analysis (adjusted HR 1.89 [95% CI: 0.95-3.73], P = .069). When comparing outcomes according to age and luminal subtypes, patients with luminal B subtype and age <40 years (n = 60) showed significantly worse outcomes compared to the others (luminal A or luminal B + age ≥40 years, n = 494; adjusted HR 2.95 [95% CI: 1.49-5.82], log-rank P < .001). Among patients with luminal B subtype and age <40 years, there was no significant association observed between IBCFS and the RS (log-rank P = .51). In conclusion, while RS >25 showed association with poor outcomes in premenopausal women, it may have less prognostic significance among those with luminal B subtype and age <40 years.

This study aimed to evaluate the long-term outcomes of stage I breast cancer (BC) patients diagnosed during the current era of screening mammography, immunohistochemistry receptor testing, and systemic adjuvant therapy.

A retrospective cohort study was conducted on 328 stage I BC patients treated consecutively in a single referral center with a follow-up period of at least 12 years. The primary endpoints were invasive disease-free survival (IDFS) and overall survival (OS). The influence of tumor size, grade, and subtype on the outcomes was analyzed.

Most patients were treated by lumpectomy, sentinel node biopsy, and adjuvant endocrine therapy, and most (82%) were of subtype luminal A. Adjuvant chemotherapy was administered to 25.6% of our cohort. Only 24 patients underwent gene expression testing, which was introduced toward the end of the study period. Mean IDFS was 14.64 years, with a 15-year IDFS of 75.6%. Mean OS was 15.28 years with a 15-year OS of 74.9%. In a Cox multivariate analysis, no clinical or pathologic variable impacted on OS and only tumor size (<1 cm vs. 1-2 cm) impacted significantly on IDFS. During follow-up, 20.1% of the cohort developed second primary cancers, including BC. The median time to diagnosis of a second BC was 6.49 years.

The study results emphasize the importance of long-term follow-up and screening for subsequent malignancies of patients with stage I BC and support the need for using prognostic and predictive indicators beyond the routine clinicopathological characteristics in luminal A patients.

Identification of the gene expression state of a cancer patient from routine pathology imaging and characterization of its phenotypic effects have significant clinical and therapeutic implications. However, prediction of expression of individual genes from whole slide images (WSIs) is challenging due to co-dependent or correlated expression of multiple genes. Here, we use a purely data-driven approach to first identify groups of genes with co-dependent expression and then predict their status from WSIs using a bespoke graph neural network. These gene groups allow us to capture the gene expression state of a patient with a small number of binary variables that are biologically meaningful and carry histopathological insights for clinical and therapeutic use cases. Prediction of gene expression state based on these gene groups allows associating histological phenotypes (cellular composition, mitotic counts, grading, etc.) with underlying gene expression patterns and opens avenues for gaining biological insights from routine pathology imaging directly.

The clinical value of tumor infiltrating lymphocytes (TILs) in hormone receptor-positive (HR+)/HER2- breast cancer (BC) may be unearthed by focusing on more biologically aggressive tumors. Here we deepen and describe the correlation between RS and TILs, proposing an immuno-genomic model for HR+ /HER2- BC.

We enrolled T1-T3, N0-N1 BC patients with available RS® and TILs in the context of four multicenter, prospective studies. RS® and TILs were considered as continuous and categorical variables. RS® was categorized into: 0-10 (low risk), 11-25 (intermediate risk) and 26-100 (high risk); TILs were categorized into: low TILs (0-10%), intermediate TILs (11-59%) and high TILs (60-100%).

811 patients were included. RS distribution was (n = 810): low risk 22.0%, intermediate risk 61.2%, high risk 16.8%. TIL distribution was (n = 455): low TILs 84.6%, intermediate TILs 13.6% and high TILs 1.8%. A significant, weak positive, linear correlation was found between continuous TILs and RS (Pearson coefficient=0.223, p < 0.001). When considering RS and TILs categories, tumors with intermediate/high TIL levels significantly enriched the high RS subgroup (p = 0.006). This was confirmed both within Luminal A and Luminal B cohorts. Among high-RS patients, 16.7% of Luminal A and 26.7% of Luminal B tumors had intermediate/high TILs.

We observed that RS® and TILs capture only slightly overlapping information on the biology of HR+ /HER2- tumor microenvironment. We demonstrated the feasibility of combining RS and TILs into a composite immuno-genomic model, which may serve the purpose of guiding and focalizing patient selection in the further development of immunotherapy strategies for Luminal-like disease.

We present a practical guide for the analysis of regression discontinuity (RD) designs in biomedical contexts. We begin by introducing key concepts, assumptions, and estimands within both the continuity-based framework and the local randomization framework. We then discuss modern estimation and inference methods within both frameworks, including approaches for bandwidth or local neighborhood selection, optimal treatment effect point estimation, and robust bias-corrected inference methods for uncertainty quantification. We also overview empirical falsification tests that can be used to support key assumptions. Our discussion focuses on two particular features that are relevant in biomedical research: (i) fuzzy RD designs, which often arise when therapeutic treatments are based on clinical guidelines, but patients with scores near the cutoff are treated contrary to the assignment rule; and (ii) RD designs with discrete scores, which are ubiquitous in biomedical applications. We illustrate our discussion with three empirical applications: the effect CD4 guidelines for anti-retroviral therapy on retention of HIV patients in South Africa, the effect of genetic guidelines for chemotherapy on breast cancer recurrence in the United States, and the effects of age-based patient cost-sharing on healthcare utilization in Taiwan. Complete replication materials employing publicly available data and statistical software in Python, R and Stata are provided, offering researchers all necessary tools to conduct an RD analysis.

Although adjuvant breast radiotherapy has long been a universal component of breast conservation therapy (BCT), it is now clear that "breast cancer" is a broad class of many disparate diseases with varying natural histories and risk profiles. In turn, some breast conservation patients enjoy exceedingly favorable outcomes following surgery alone. Ongoing trials seek to identify such low-risk patient populations, hypothesizing that some may safely forego radiotherapy. Whereas prior-generation trials focused on clinicopathologic features for risk stratification, contemporary studies are employing molecular biomarkers to identify those patients who are unlikely to benefit significantly from radiotherapy.

Clinical trial design must consider the specific resource constraints and overall goals of the drug development process (DDP); for example, in designing a phase I trial to evaluate the safety of a drug and recommend a dose for a subsequent phase II trial. Here, we focus on design considerations that involve the sequence of clinical trials, from early phase I to late phase III, that constitute the DDP.

We discuss how stylized simulation models of clinical trials in an oncology DDP can quantify important relationships between early-phase trial designs and their consequences for the remaining phases of development. Simulations for three illustrative settings are presented, using stylized models of the DDP that mimic trial designs and decisions, such as the potential discontinuation of the DDP.

We describe: (1) the relationship between a phase II single-arm trial sample size and the likelihood of a positive result in a subsequent phase III confirmatory trial; (2) the impact of a phase I dose-finding design on the likelihood that the DDP will produce evidence of a safe and effective therapy; and (3) the impact of a phase II enrichment trial design on the operating characteristics of a subsequent phase III confirmatory trial.

Stylized models of the DDP can support key decisions, such as the sample size, in the design of early-phase trials. Simulation models can be used to estimate performance metrics of the DDP under realistic scenarios; for example, the duration and the total number of patients enrolled. These estimates complement the evaluation of the operating characteristics of early-phase trial design, such as power or accuracy in selecting safe and effective dose levels.

Generalizable population-based studies are unable to account for individual tumor heterogeneity that contributes to variability in a patient's response to physician-chosen therapy. Although molecular characterization of tumors has advanced precision medicine, in early-stage and locally advanced breast cancer patients, predicting a patient's response to neoadjuvant therapy (NAT) remains a gap in current clinical practice. Here, we perform a study in an independent cohort of early-stage and locally advanced breast cancer patients to forecast tumor response to NAT and assess the stability of a previously validated biophysical simulation platform.

A single-blinded study was performed using a retrospective database from a single institution (9/2014-12/2020). Patients included: ≥ 18 years with breast cancer who completed NAT, with pre-treatment dynamic contrast enhanced magnetic resonance imaging. Demographics, chemotherapy, baseline (pre-treatment) MRI and pathologic data were input into the TumorScope Predict (TS) biophysical simulation platform to generate predictions. Primary outcomes included predictions of pathological complete response (pCR) versus residual disease (RD) and final volume for each tumor. For validation, post-NAT predicted pCR and tumor volumes were compared to actual pathological assessment and MRI-assessed volumes. Predicted pCR was pre-defined as residual tumor volume ≤ 0.01 cm³ (≥ 99.9% reduction).

The cohort consisted of eighty patients; 36 Caucasian and 40 African American. Most tumors were high-grade (54.4% grade 3) invasive ductal carcinomas (90.0%). Receptor subtypes included hormone receptor positive (HR+)/human epidermal growth factor receptor 2 positive (HER2+, 30%), HR+/HER2- (35%), HR-/HER2+ (12.5%) and triple negative breast cancer (TNBC, 22.5%). Simulated tumor volume was significantly correlated with post-treatment radiographic MRI calculated volumes (r = 0.53, p = 1.3 × 10^-7, mean absolute error of 6.57%). TS prediction of pCR compared favorably to pathological assessment (pCR: TS n = 28; Path n = 27; RD: TS n = 52; Path n = 53), for an overall accuracy of 91.2% (95% CI: 82.8% - 96.4%; Clopper-Pearson interval). Five-year risk of recurrence demonstrated similar prognostic performance between TS predictions (Hazard ratio (HR): - 1.99; 95% CI [- 3.96, - 0.02]; p = 0.043) and clinically assessed pCR (HR: - 1.76; 95% CI [- 3.75, 0.23]; p = 0.054).

We demonstrated TS ability to simulate and model tumor in vivo conditions in silico and forecast volume response to NAT across breast tumor subtypes.

Numerous clinical trials have reported equal effects of tumor control between neoadjuvant chemotherapy (NAC) and adjuvant chemotherapy (AC) in patients with breast cancer (BC). However, this conclusion has not been verified in practice. The present retrospective study evaluated if there were different risk profiles for NAC, AC and their combinative modes on disease-free survival (DFS) in patients with BC using real-world data. All women with primary unilateral Stage I-III BC and first recurrence in 2008-2018 at The Fourth Hospital of Hebei Medical University were retrospectively identified for enrollment. The four modes of chemotherapy administered for primary BC were classified as 'None', 'NAC only', 'NAC+AC' and 'AC only'. One multivariate Cox model was used to estimate the adjusted Hazard Ratio (HR) and P-value. Covariates included age, Easter Cooperative Oncology Group grade, T stage, N stage, pathology, grade, lymphovascular invasion (LVI), BC subtype, number of chemotherapy cycles and other therapies. Amongst 637 patients, who had a mean age of 48.2 years at BC diagnosis and 50.9 years at recurrence, the median DFS by the 'None' (n=27), 'NAC only' (n=47), 'NAC+AC' (n=118) and 'AC only' (n=445) modes were 31.4, 16.6, 22.6 and 28.4 months (P<0.001), respectively. Compared with the 'AC only', adjusted HR (P-value) of the 'None', 'NAC only' and 'NAC+AC' modes on tumor recurrence were 1.182 (0.551), 1.481 (0.037) and 1.102 (0.523), respectively. The adjusted HR of 'NAC only' vs. 'AC only' modes were 1.448 (P=0.157) for locoregional recurrence and 2.675 (P=0.003) for distant recurrence. Stratified analyses further indicated that the 'NAC only' mode was associated with a higher recurrence risk in T3-4, N2-3, LVI-positive, or HER2-negative subgroup patients. In conclusion, NAC alone was associated with a higher risk of tumor recurrence in high-risk BC subgroup patients in real-world data. Patient selection of chemotherapy mode was involved in practice but could not fully explain this finding. The 'inadequate' NAC was highly likely to have accounted for this observation.

Hormone receptor (HR)-positive, HER2/neu-negative breast cancers have a sustained risk of recurrence up to 20 years from diagnosis. TEAM (Tamoxifen, Exemestane Adjuvant Multinational) is a large, multi-country, phase III trial that randomized 9776 women for the use of hormonal therapy. Of these 2754 were Dutch patients. The current study aims for the first time to correlate the ten-year clinical outcomes with predictions by CanAssist Breast (CAB)-a prognostic test developed in South East Asia, on a Dutch sub-cohort that participated in the TEAM. The total Dutch TEAM cohort and the current Dutch sub-cohort were almost similar with respect to patient age and tumor anatomical features.

Of the 2754 patients from the Netherlands, which are part of the original TEAM trial, 592 patients' samples were available with Leiden University Medical Center (LUMC). The risk stratification of CAB was correlated with outcomes of patients using logistic regression approaches entailing Kaplan-Meier survival curves, univariate and multivariate cox-regression hazards model. We used hazard ratios (HRs), the cumulative incidence of distant metastasis/death due to breast cancer (DM), and distant recurrence-free interval (DRFi) for assessment.

Out of 433 patients finally included, the majority, 68.4% had lymph node-positive disease, while only a minority received chemotherapy (20.8%) in addition to endocrine therapy. CAB stratified 67.5% of the total cohort as low-risk [DM = 11.5% (95% CI, 7.6-15.2)] and 32.5% as high-risk [DM = 30.2% (95% CI, 21.9-37.6)] with an HR of 2.90 (95% CI, 1.75-4.80; P < 0.001) at ten years. CAB risk score was an independent prognostic factor in the consideration of clinical parameters in multivariate analysis. At ten years, CAB high-risk had the worst DRFi of 69.8%, CAB low-risk in the exemestane monotherapy arm had the best DRFi of 92.7% [vs CAB high-risk, HR, 0.21 (95% CI, 0.11-0.43), P < 0.001], and CAB low-risk in the sequential arm had a DRFi of 84.2% [vs CAB high-risk, HR, 0.48 (95% CI, 0.28-0.82), P = 0.009].

Cost-effective CAB is a statistically robust prognostic and predictive tool for ten-year DM for postmenopausal women with HR+/HER2-, early breast cancer. CAB low-risk patients who received exemestane monotherapy had an excellent ten-year DRFi.

Oncotype DX (ODX) is a well-validated multigene assay that is increasingly used in Korean clinical practice. This study aimed to develop a clinicopathological prediction (CPP) model for the ODX recurrence scores (RSs).

A total of 297 patients (study group, n = 175; external validation group, n = 122) with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, T1-3N0-1M0 breast cancer, and available ODX test results were included in the study. Risk categorization as determined by ODX RSs concurred with the TAILORx study (low-risk, RS ≤ 25; high-risk, RS > 25). Univariate and multivariate logistic regression analyses were used to assess the relationships between clinicopathological variables and risk stratified by the ODX RSs. A CPP model was constructed based on regression coefficients (β values) for clinicopathological variables significant by multivariate regression analysis.

Progesterone receptor (PR) negativity, high Ki-67 index, and nuclear grade (NG) 3 independently predicted high-risk RS, and these variables were used to construct the CPP model. The C-index, which represented the discriminatory ability of our CPP model for predicting a high-risk RS, was 0.915 (95% confidence interval [CI], 0.859-0.971). When the CPP model was applied to the external validation group, the C-index was 0.926 (95% CI, 0.873-0.978).

Our CPP model based on PR, Ki-67 index, and NG could aid in the selection of patients with breast cancer requiring an ODX test.

While endocrine therapy is the standard-of-care adjuvant treatment for hormone receptor-positive (HR+) breast cancers, there is also extensive evidence for the role of pre-operative (or neoadjuvant) endocrine therapy (NET) in HR+ postmenopausal women.

We conducted a thorough review of the published literature, to summarize the evidence to date, including studies of how NET compares to neoadjuvant chemotherapy, which NET agents are preferable, and the optimal duration of NET. We describe the importance of on-treatment assessment of response, the different predictors available (including Ki67, PEPI score, and molecular signatures) and the research opportunities the pre-operative setting offers. We also summarize recent combination trials and discuss how the COVID-19 pandemic led to increases in NET use for safe management of cases with deferred surgery and adjuvant treatments.

NET represents a safe and effective tool for the management of postmenopausal women with HR+/HER2- breast cancer, enabling disease downstaging and a wider range of surgical options. Aromatase inhibitors are the preferred NET, with evidence suggesting that longer regimens might yield optimal results. However, NET remains currently underutilised in many territories and institutions. Further validation of predictors for treatment response and benefit is needed to help standardise and fully exploit the potential of NET in the clinic.

Many patients with non-metastatic breast cancer benefit from adjuvant radiation therapy after lumpectomy or mastectomy on the basis of many randomized trials. However, there are many patients that have such low risks of recurrence after surgery that de-intensification of therapy by either reducing the treatment volume or omitting radiation altogether may be appropriate options. On the other hand, dose intensification may be necessary for more aggressive breast cancers. Until recently, these treatment decisions were based solely on clinicopathologic factors. Here, we review the current literature on the role of genomic assays as prognostic and/or predictive biomarkers to help guide adjuvant radiation therapy decision-making.

Copy number aberrations (CNAs) in cancer affect disease outcomes by regulating molecular phenotypes, such as gene expressions, that drive important biological processes. To gain comprehensive insights into molecular biomarkers for cancer, it is critical to identify key groups of CNAs, the associated gene modules, regulatory modules, and their downstream effect on outcomes.

In this paper, we demonstrate an innovative use of sparse canonical correlation analysis (sCCA) to effectively identify the ensemble of CNAs, and gene modules in the context of binary and censored disease endpoints. Our approach detects potentially orthogonal gene expression modules which are highly correlated with sets of CNA and then identifies the genes within these modules that are associated with the outcome.

Analyzing clinical and genomic data on 1,904 breast cancer patients from the METABRIC study, we found 14 gene modules to be regulated by groups of proximally located CNA sites. We validated this finding using an independent set of 1,077 breast invasive carcinoma samples from The Cancer Genome Atlas (TCGA). Our analysis of 7 clinical endpoints identified several novel and interpretable regulatory associations, highlighting the role of CNAs in key biological pathways and processes for breast cancer. Genes significantly associated with the outcomes were enriched for early estrogen response pathway, DNA repair pathways as well as targets of transcription factors such as E2F4, MYC, and ETS1 that have recognized roles in tumor characteristics and survival. Subsequent meta-analysis across the endpoints further identified several genes through the aggregation of weaker associations.

Our findings suggest that sCCA analysis can aggregate weaker associations to identify interpretable and important genes, modules, and clinically consequential pathways.

Breast carcinoma (BCa) remains the second most common cause of cancer-related death among American women. Whereas estrogen receptor (ER) expression is typically regarded as a favorable prognostic indicator, a significant proportion of ER(+) patients still experience either de novo or acquired endocrine resistance. Previously, we have shown that the loss of orphan nuclear receptor NURR1 expression is associated with neoplastic transformation of the breast epithelium and shorter relapse-free survival (RFS) among systemically treated breast cancer (BCa) patients. Here, we further ascertain the prognostic value of NURR1 in BCa, and its differential expression among Black and White female BCa patients. We assessed the expression of NURR1 mRNA in BCa patients using the Cancer Genome Atlas (TGCA) and compared the occurrence of basal-like cancer and luminal A breast cancer subtypes. Expression levels were further stratified according to racial identity of the patient. We next assessed the correlation of NURR1 expression with Oncotype DX prognostic markers, and the association of NURR1 expression with relapse free survival in patients treated with endocrine therapy. Our study shows that NURR1 mRNA expression is differentially correlated with luminal A vs. basal-like cancer BCa and is predictive of poor relapse-free survival, confirming a similar trend observed in our previous studies using microarray data. NURR1 expression was positively correlated with expression of Oncotype DX biomarkers associated with estrogen responsiveness, while being inversely correlated with biomarkers associated with cell proliferation. Furthermore, we observed that NURR1 expression was positively associated with greater relapse-free survival at 5 years among patients treated with endocrine therapy. Interestingly, we found that among Black women with luminal A BCa, NURR1 expression was repressed in comparison to White women with the same subtype.