American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version)

Landscape of lncRNAs expressed in Mexican patients with triple‑negative breast cancer

Long non‑coding RNAs (lncRNAs) are key regulators of gene expression, that can regulate a range of carcinogenic processes. Moreover, they exhibit stability in biological fluids, with some displaying tissue specificity. As their expression depends on specific conditions or is linked to the regulation of particular signaling pathways, lncRNAs are promising candidates for providing insights into the likely progression of the disease. This allows for the stratification of patients based on their risk of progression, making them potential prognostic biomarkers in various types of cancer. In addition, the tissue‑specific expression profile of lncRNAs renders them ideal candidates for detection, prognosis and monitoring of cancer progression. The present study aims to provide an overview of differentially expressed lncRNAs in Mexican patients with triple‑negative breast cancer (TNBC), a subtype of breast cancer. The aim was to identify potential prognostic biomarkers that can be applied to improve the clinical management of Mexican patients with TNBC. Human Transcriptome Array 2.0 microarrays were used to analyze the transcriptome of TNBC and luminal tumors, which are reported to have a good prognosis amongst aggressive tumor types. Subsequently, results from these microarrays were validated in a cohort from The Cancer Genome Atlas, an independent cohort of Mexican patients and in breast cancer cell lines (MCF7, ZR75, T47D, MDA‑MB‑231, MDA‑MB‑468 and BT20). A total of 746 differentially expressed transcripts were identified, including 102 lncRNAs in TNBC compared with luminal tumors. Among the lncRNAs with the most significant changes in expression levels, SOX9‑AS was highly expressed in TNBC, whereas the expression of Lnc‑peroxidasin‑3:1 (Lnc‑PXDN‑3:1), Lnc‑RNA Synapse Defective Rho GTPase Homolog (Lnc‑SYDE) and long intergenic non‑coding RNA (LINC)01087 were decreased. In addition, the low expression of lncRNA LINC01087, LINC02568, ACO22196, and lncRNA eosinophil granule ontogeny transcript (Lnc‑EGOT) was associated with poor overall survival (OS). Further analysis revealed that the high expression levels of Lnc‑PXDN‑3:1, Lnc RNA fibrous sheath interacting protein 1‑6:3 and (LINC)00182 were associated with reduced survival in patients with the luminal subtype of breast cancer. Similarly, low expression levels of lncRNAs such as GATA binding protein 3‑1 (Lnc‑GATA‑3‑1), LINC01087, and BX679671.1 in luminal subtypes of breast cancer, as well as LINC00504 and LncRNA rho guanine nucleotide exchange factor 38 intronic transcript 1 (Lnc‑ARHGEF38‑IT1) in basal subtypes have been linked to poorer survival. The interactions and functions of LINC01087 were then investigated, revealing the interaction of LINC01087 with RNAs and transcription factors, highlighting their potential involvement in the estrogen receptor pathway. The present study provided a detailed analysis of the expression of lncRNAs in TNBC, which highlights the role of lncRNAs as a biomarker in the survival outcomes of patients with breast cancer to improve the understanding of transcriptional regulation in TNBC.

Novel MRI-based Hyper-Fused Radiomics for Predicting Pathologic Complete Response to Neoadjuvant Therapy in Breast Cancer

RATIONALE AND OBJECTIVES

To propose a novel MRI-based hyper-fused radiomic approach to predict pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer (BC).

MATERIALS AND METHODS

Pretreatment dynamic contrast-enhanced (DCE) MRI and ultra-multi-b-value (UMB) diffusion-weighted imaging (DWI) data were acquired in BC patients who received NAT followed by surgery at two centers. Hyper-fused radiomic features (RFs) and conventional RFs were extracted from DCE-MRI or UMB-DWI. After feature selection, the following models were built using logistic regression and the retained RFs: hyper-fused model, conventional model, and compound model that integrates the hyper-fused and conventional RFs. The output probability of each model was used to generate a radiomic signature. The model's performance was quantified by the area under the receiver-operating characteristic curve (AUC). Multivariable logistic regression was used to identify variables (clinicopathological variables and the generated radiomic signatures) associated with pCR.

RESULTS

The training/external test set (center 1/2) included 547/295 women. The hyper-fused models (AUCs=0.81-0.85) outperformed (p<0.05) the conventional models (AUCs=0.74-0.80) in predicting pCR. The compound models (AUCs=0.88-0.93) outperformed (p<0.05) the hyper-fused models and conventional models for pCR prediction. The hyper-fused radiomic signatures (odds ratios=5.70-12.98; p<0.05) and compound radiomic signatures (odds ratios=1.57-7.71; p<0.05) were independently associated with pCR. These are true for the training and external test sets.

CONCLUSION

The hyper-fused radiomic approach had significantly better performance for predicting pCR to NAT than the conventional radiomic approach, and the hyper-fused RFs provided incremental discrimination of pCR beyond the conventional RFs. The generated hyper-fused radiomic signatures were independent predictors of pCR.

Quantitative proteomics analysis of triple-negative breast cancers

Triple-negative breast cancer (TNBC) accounts for approximately 15% of all Breast Cancer (BC) cases with poorer prognosis and clinical outcomes compared to other BC subtypes due to greater tumor heterogeneity and few therapeutically targetable oncogenic drivers. To reveal actionable pathways for anti-cancer treatment, we use a proteomic approach to quantitatively compare the abundances of 6306 proteins across 55 formalin-fixed and paraffin-embedded (FFPE) TNBC tumors. We identified four major TNBC clusters by unsupervised clustering analysis of protein abundances. Analyses of clinicopathological characteristics revealed associations between the proteomic profiles and clinical phenotypes exhibited by each subtype. We validate the findings by inferring immune and stromal cell type composition from genome-wide DNA methylation profiles. Finally, quantitative proteomics on TNBC cell lines was conducted to identify in vitro models for each subtype. Collectively, our data provide subtype-specific insights into molecular drivers, clinicopathological phenotypes, tumor microenvironment (TME) compositions, and potential pharmacologic vulnerabilities for further investigations.

Is It Possible to Accurately Evaluate the Tumor Bed After Neoadjuvant Chemotherapy Using a 14G Tru-Cut Biopsy?

Background/Objectives: Accurately identifying residual disease in the breast following neoadjuvant systemic therapy (NST) is a critical aspect of treatment planning. While surgery remains the standard treatment, its omission may be considered in exceptional responders. However, this strategy is still under investigation and carries local and distant recurrence risks. No definitive method currently exists to confirm pathologic complete response (pCR) after NST. This study evaluates the reliability of ultrasound-guided 14G Tru-Cut biopsy in assessing post-NST disease status. Methods: Data from 204 breast cancer patients who underwent ultrasound-guided 14G Tru-Cut biopsy before surgery at Istanbul University Oncology Institute (March 2015-May 2024) were analyzed. Concordance between Tru-Cut biopsy and final pathology was assessed, along with diagnostic accuracy parameters, including false-negative rate (FNR), accuracy, negative predictive value (NPV), and positive predictive value (PPV). Results: The median patient age was 45 years (range: 26-86). The median initial tumor size was 32 mm, reducing to 10 mm post-treatment. Pathologic complete response (pCR) was 33.8% in surgical specimens and 40.7% in biopsy samples. Biopsy misdiagnosed 15 patients, with an overall FNR of 11.1% and accuracy of 92.2% (95% CI, 7.1-18.1%; 95% CI, 87.6-95.5%). Among patients with radiologic complete response (rCR) (n = 99), FNR was 25.8%, and accuracy was 92.1%. The best outcomes were in the rCR and Tru-Cut pCR subgroup, with an FNR of 5.9% and accuracy of 95.6%. In triple-negative breast cancer patients, FNR was 5%, and an accuracy was 97.4%. Conclusions: Although obtaining eight or more samples with a 14G Tru-Cut biopsy after NST is insufficient to alter clinical practice for detecting residual disease, the promising results observed in the rCR and Tru-Cut pCR subgroups suggest its potential role in guiding treatment strategies.

Serous-like breast carcinomas: immunophenotypic, genetic, and clinicopathologic characterization of a morphologically distinct group of tumours

AIMS

Unusual morphologic patterns of breast carcinomas can raise diagnostic consideration for metastasis or special breast cancer subtypes with management implications. We describe rare invasive breast cancers that mimic serous carcinoma of the gynaecologic tract (serous-like breast carcinomas, SLBC) and characterize their clinicopathologic, immunophenotypic, and genetic features.

METHODS AND RESULTS

All patients were female (n = 15, median age 49 years) without a history of gynaecologic malignancy. SLBC were characterized histologically by angulated, branched, sometimes anastomosing glands with micropapillary and/or pseudopapillary luminal projections in desmoplastic stroma. Most SLBC were triple-negative (TN, n = 10) or HER2-positive (n = 2) and grade 2 or 3, while some were oestrogen receptor (ER) low-positive/HER2-negative and low-grade (n = 3). CK5/6 was positive irrespective of grade or receptor status (10/10). All SLBC expressed GATA3 (14/15), TRPS1 (7/7), and/or mammaglobin (4/13). SOX10 was positive in most TN (9/10) and all ER low-positive (3/3) cases, but negative in HER2-positive tumours. WT1 was universally negative, and PAX8 was focal in one mammaglobin-positive tumour. All ER-negative SLBC were p53-aberrant and 9/11 were p16-aberrant, whereas ER-positive tumours were wildtype for both markers (3/3). TP53 was the only frequently mutated gene, altered in all ER-negative (10/10) but no ER-positive (0/4) tumours. Clinical behaviour was variable. Only 1/6 patients achieved pathologic complete response to neoadjuvant chemotherapy.

CONCLUSION

SLBC is a rare morphologic pattern of invasive breast carcinoma that mimics metastatic serous gynaecologic carcinoma, a potential diagnostic pitfall. SLBC are heterogeneous with respect to grade, receptor profile, and oncogenic driver alterations, without specific genetic underpinnings identified. Additional studies are warranted to further evaluate the clinical behaviour of these tumours.

Systematic Review of Soft Tissue Sarcomas in Latin America

PURPOSE

Soft tissue sarcomas (STSs) are rare malignant neoplasms posing significant public health challenges globally, especially in Latin America with limited research resources. This systematic review provides an overview of the epidemiology, clinical characteristics, treatment, and outcomes of STSs in Latin America, emphasizing the impact of insufficient investment in research and health care infrastructure.

MATERIALS AND METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic literature review of clinicopathologic characteristics of STSs in Latin American patients. Studies published between January 1986 and August 2024 were included. A comprehensive search across multiple databases yielded 502 papers, refined to 18 publications and three national records included in the study. A meta-analysis was done for survival evaluation.

RESULTS

Data from 2,931 patients with mean age 47 years were analyzed, and 340 patients had pretreatment biopsy. The most common sarcoma types were liposarcoma (23.2%) and synovial sarcoma (21.2%), with high-grade tumors (52%) predominating. Treatment primarily involved surgery (863 patients), often combined with radiotherapy (559 patients) and chemotherapy (307 patients). Five-year overall survival was 61%.

DISCUSSION

The findings highlight challenges in managing STSs in Latin America, including advanced disease at diagnosis and high-grade tumors. Survival rates correlate with local advanced disease reported by other countries. Barriers include limited access to specialized centers and inadequate use of preoperative biopsies. Improved diagnostic and treatment strategies and collaborations to enhance research and clinical practices are needed.

CONCLUSION

This review underscores critical gaps in STS management in Latin America. Increased investment in research, a cohesive network of specialized care centers, and a multidisciplinary approach are essential to improve outcomes and quality of life for patients in the region.

Potential biological roles of exosomal non-coding RNAs in breast cancer

Breast cancer (BC) is one of the most common malignant tumors among women, accounting for 24.5% of all cancer cases and leading to 15.5% of cancer-related mortality. The treatment of BC patients remains a significant challenge due to the disease's high invasiveness, elevated metastatic potential, substantial drug resistance, and high recurrence rate. Exosomes, which are lipid-bilayer extracellular vesicles ranging in size from 30 to 150 nm, mediate intercellular communication between tumor cells and surrounding cells in the tumor microenvironment by transferring various bioactive substances, such as proteins, lipids, and nucleic acids. Recently, growing evidence has demonstrated that non-coding RNAs (ncRNAs) are enriched in exosomes and play a critical role in regulating cell proliferation, metastasis, drug resistance, and angiogenesis in BC. Consequently, exosomal ncRNAs have emerged as a promising therapeutic target for BC treatment, given their involvement in multiple processes of cancer progression. This review provides a comprehensive and in-depth analysis of emerging exosomal ncRNAs in BC, highlighting their potential biological mechanisms and advanced applications in BC treatment.

ZNF703 promotes Triple-Negative breast cancer cell progression and in combination with STK11 predicts disease recurrence (ZS -TNBC Model)

BACKGROUND

It is largely unidentified concerning the underlying genetic causes responsible for triple-negative breast cancers (TNBC), with unpredictable disease recurrence. This study aimed to examine the role of ZNF703 (Zinc finger 703) in the malignant behaviors of TNBC and its role in predicting disease-free survival (DFS).

METHODS

After downregulation of ZNF703 with short interfering RNA (siRNA), we examined the proliferation of TNBC cell line MDA-MB-231 by sulforhodamine B (SRB) assay, the invasion of cells by a transwell invasion model, and the migration of cells by the monolayer wound-healing experiment. mRNA-sequencing data of ZNF703, BRCA1, BRCA2, PALB2, CHEK2, CDH1, PTEN, STK11, ATM, and TP53, and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset for a total of 157 stage I-III TNBC samples. The selection of modeling features was executed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm to avoid model overfitting. The TIMER 2.0 algorithm determined the associations between immune score and gene expressions. Kaplan-Meier analysis was conducted to plot survival analyses.

RESULTS

The aggressive tumor morphology, cell proliferation, cell migration, and cell invasion were partly reversed by the siRNA knockdown of ZNF703 in MDA-MB-231 cells. ZNF703 knockdown markedly enhanced the killing ability of cisplatin These phenomena were verified by another TNBC cell line BT-549. Patients with high expression of ZNF703 had an inferior DFS for TNBC patients at 8 years [Hazard ratio (HR) for high expression vs. low expression was 2.71; 95 %CI, 1.03 to 7.14, P = 0.044]. Receiver Operating Characteristic (ROC) curve was also developed, indicating the area under the curve (AUC) was 0.744 (95 %CI, 0.628 to 0.861) at 5 years and 0.738 (95 %CI, 0.552 to 0.924) at 8 years, respectively. In addition, LASSO regression results showed that the optimal penalization parameter corresponds to two prognostic genes - ZNF703 and STK11. The risk score was computed as Risk Score (RS) = 0.1033*ZNF703 + 0.2131*STK11 (named "ZS -TNBC model"). The high expression of both ZNF703 and STK11 had as high as 7.035 HR in comparison to the low-expression category (95 %CI, 2.044 to 24.206, P = 0.00197).

CONCLUSION

ZNF703 is required for the growth, invasion, and migratory behavior of TNBC cells. Downregulation of ZNF703 increases cisplatin efficacy. This study suggests that either ZNF703 alone or in conjunction with STK11 can be utilized to predict DFS in TNBC.

Bi-level graph learning unveils prognosis-relevant tumor microenvironment patterns in breast multiplexed digital pathology

The tumor microenvironment (TME) is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. Increasing efforts have been dedicated to characterizing it, including its analysis with modern deep learning. However, identifying generalizable biomarkers has been limited by the uninterpretable nature of their predictions. We introduce a data-driven yet interpretable approach for identifying cellular patterns in the TME associated with patient prognoses. Our method relies on constructing a bi-level graph model: a cellular graph, which models the TME, and a population graph, capturing inter-patient similarities given their respective cellular graphs. We demonstrate our approach in breast cancer, showing that the identified patterns provide a risk-stratification system with new complementary information to standard clinical subtypes, and these results are validated in two independent cohorts. Our methodology could be applied to other cancer types more generally, providing insights into the spatial cellular patterns associated with patient outcomes.

The Diagnostics of Disease Relapse Within Five-Year Follow-Up and the Role of Androgen Receptor Expression in Patients with Early Triple-Negative Breast Cancer

Background/Objectives: Triple-negative breast cancer (TNBC) is characterized by the absence of the expression of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2. As there are no specific targeted therapies, TNBC patients often face an aggressive clinical course. The expression of the androgen receptor (AR) has been found in up to 30% of TNBC cases, but the association between the AR status and survival rates in TNBC remains controversial. The aim of this study was to explore the association of AR expression with the disease outcome in patients with early TNBC within a 5-year follow-up. Methods: AR expression was determined by immunohistochemistry in a cohort of 124 early-TNBC patients treated at the Institute for Oncology and Radiology of Serbia. The cut-off value used for the positive AR status was >10% tumor cells. The association of the AR status with clinicopathological factors (age, stage, tumor diameter, lymph node invasion, metastatic spread, Ki-67 score, EGFR score, and cytokeratin 5/6 score) and the disease outcome (disease-free survival-DFS-and overall survival-OS) was investigated. Results: Our analysis showed that the AR-positive status was associated with a significantly lower Ki-67 score compared to the AR-negative samples. A univariate analysis indicated that the age, tumor size, nodal status, and EGFR score significantly influenced both 5-year DFS and OS. Multivariate Cox analysis suggested that a smaller tumor size, lower nodal status, and AR expression were independent predictors of longer survival rates in TNBC patients. Conclusions: The results of this study suggest that the positive AR status may be a favorable prognostic factor in TNBC patients within the first five years after surgery.

Rare Histological Types of Breast Cancer: A Single-Center Experience

Background: Breast carcinoma is divided into at least 21 separate histologies, according to the 2019 World Health Organization (WHO) classification. The present study is dedicated to a 5% or rarer group of all breast cancer cases. Method: In this study, we retrospectively considered the data of 4550 patients operated on for breast carcinoma at the Ankara Oncology Training and Research Hospital of the University of Health Sciences between January 2018 and February 2024. Of those cases, 401 were discovered to have rare breast cancer types. We also explored the cases by clinicopathological features, overall survival (OS), and disease-free survival (DFS). Results: Our findings revealed a total of 10 rare breast cancer types in patients explored: mucinous carcinoma, micropapillary carcinoma, papillary group carcinomas, metaplastic carcinoma, neuroendocrine carcinoma, tubular carcinoma, cribriform carcinoma, apocrine carcinoma, acinic cell carcinoma, and secretory carcinoma. While mucinous, tubular, cribriform, papillary group carcinomas, micropapillary, and secretory carcinomas are described as types associated with good prognosis, metaplastic, neuroendocrine, apocrine, and carcinomas are described as types associated with relatively poor prognosis. Conclusion: Scrutinizing the clinicopathological features of rare breast cancer types altogether may be the distinct contribution of this paper to the relevant literature and future research.

Intratumoral and peritumoral ultrasound-based radiomics for preoperative prediction of HER2-low breast cancer: a multicenter retrospective study

OBJECTIVES

Recent advances in human epidermal growth factor receptor 2 (HER2)-targeted therapies have opened up new therapeutic options for HER2-low cancers. This study aimed to establish an ultrasound-based radiomics model to identify three different HER2 states noninvasively.

METHODS

Between May 2018 and December 2023, a total of 1257 invasive breast cancer patients were enrolled from three hospitals. The HER2 status was divided into three classes: positive, low, and zero. Four peritumoral regions of interest (ROI) were auto-generated by dilating the manually segmented intratumoral ROI to thicknesses of 5 mm, 10 mm, 15 mm, and 20 mm. After image preprocessing, 4720 radiomics features were extracted from each image of every patient. The least absolute shrinkage and selection operator and LightBoost algorithm were utilized to construct single- and multi-region radiomics signatures (RS). A clinical-radiomics combined model was developed by integrating discriminative clinical-sonographic factors with the optimal RS. A data stitching strategy was used to build patient-level models. The Shapley additive explanations (SHAP) approach was used to explain the contribution of internal prediction.

RESULTS

The optimal RS was constructed by integrating 12 tumor features and 9 peritumoral-15mm features. Age, tumor size, and seven qualitative ultrasound features were retained to construct the clinical-radiomics combined model with the optimal RS. In the training, validation, and test cohorts, the patient-level combined model showed the best discrimination ability with the macro-AUCs of 0.988 (95% CI: 0.983-0.992), 0.915 (95% CI: 0.851-0.965), and 0.862 (95% CI: 0.820-0.899), respectively.

CONCLUSION

This study built a robust and interpretable clinical-radiomics model to evaluate three classes of HER2 status based on ultrasound images.

CRITICAL RELEVANCE STATEMENT

Ultrasound-based radiomics method can noninvasively identify three different states of HER2, which may guide treatment decisions and the implementation of personalized HER2-targeted treatment for invasive breast cancer patients.

KEY POINTS

Determination of HER2 status can affect treatment options for breast cancer. The ultrasound-based clinical-radiomics model can discriminate the three different HER2 statuses. Our developed model can assist in providing personalized recommendations for novel HER2-targeted therapies.

Superior performance in classification of breast cancer molecular subtype and histological factors by radiomics based on ultrafast MRI over standard MRI: evidence from a prospective study

PURPOSE

To compare the performance of ultrafast MRI with standard MRI in classifying histological factors and subtypes of invasive breast cancer among radiologists with varying experience.

METHODS

From October 2021 to November 2022, this prospective study enrolled 225 participants with 233 breast cancers before treatment (NCT06104189 at clinicaltrials.gov). Tumor segmentation on MRI was performed independently by two readers (R1, dedicated breast radiologist; R2, radiology resident). We extracted 1618 radiomic features and four kinetic features from ultrafast and standard images, respectively. Logistic regression algorithms were adopted for prediction modeling, following feature selection by the least absolute shrinkage and selection operator. The performance of predicting histological factors and subtypes was evaluated using the area under the receiver-operating characteristic curve (AUC). Performance differences between MRI methods and radiologists were assessed using the DeLong test.

RESULTS

Ultrafast MRI outperformed standard MRI in predicting HER2 status (AUCs [95% CI] of ultrafast MRI vs standard MRI; 0.87 [0.83-0.91] vs 0.77 [0.64-0.90] for R1 and 0.88 [0.83-0.91] vs 0.77 [0.69-0.84] for R2) (all P < 0.05). Both ultrafast MRI and standard MRI showed comparable performance in predicting hormone receptors. Ultrafast MRI exhibited superior performance to standard MRI in classifying subtypes. The classification of the luminal subtype for both readers, the HER2-overexpressed subtype for R2, and the triple-negative subtype for R1 was significantly better with ultrafast MRI (P < 0.05).

CONCLUSION

Ultrafast MRI-based radiomics holds promise as a noninvasive imaging biomarker for classifying hormone receptors, HER2 status, and molecular subtypes compared to standard MRI, regardless of radiologist experience.

Quality Assurance Model for Breast Cancer Prognostication Using the Modified Magee Equations

CONTEXT.—

The Oncotype DX recurrence score (RS) is a widely used test that provides prognostic information on the likelihood of disease recurrence and predictive information on the benefit of chemotherapy in early-stage, hormone receptor-positive breast cancer. Despite its widespread use, quality assurance of the RS does not receive the same level of scrutiny as other tests, such as human epidermal growth factor receptor 2 (HER2) immunohistochemistry.

OBJECTIVE.—

To use modified Magee equations to calculate the Magee score (MS) as a quality check of RS.

DESIGN.—

The MS is an easily accessible prognostic model that uses histopathologic and immunohistochemical criteria. We identified cases where the RS and MS differed by 10 points or more or were in different risk categories. These instances were considered significant discordances. MS was presented along with RS at multidisciplinary tumor boards, and all discrepancies were discussed to determine clinical significance and appropriate next steps.

RESULTS.—

Twenty-five of 155 cases (16.1%) had discrepancies between RS and MS. Of these 25 cases, 3 (12%) had problems with either the RS or the histopathologic interpretation. Among the cases with concordant RS and MS, no RS or interpretive problems were identified.

CONCLUSIONS.—

Use of the MS as a quality control check for the RS can help ensure appropriate treatment decisions in breast cancer patients. Pathologists can play a key role in ensuring the quality of molecular-based prognostic scores by using histopathologic models to ensure accurate risk stratification and improve clinical outcomes.

Elacestrant in hormone receptor-positive metastatic breast cancer: a post-hoc analysis

Background

Breast cancer is a leading cause of mortality in women. Hormone therapy plays a crucial role in treatment of hormone receptor-positive metastatic breast cancer. Elacestrant is a selective estrogen receptor degrader (SERD) that has shown promise in early-phase clinical trials. This post-hoc analysis systematically evaluates elacestrant's effectiveness in hormone receptor-positive metastatic breast cancer patients, providing insights into its efficacy, safety, and potential advantages over existing treatments.

Methods

We adhered to the PRISMA Statement 2020 guidelines and systematically searched the databases PubMed/MEDLINE, ClinicalTrials.gov, Web of Science, and Embase. We conducted the post-hoc analysis using R software (V 4.3.3), applying the inverse variance method and the DerSimonian-Laird estimator to pool effect estimates with a random-effects model. We assessed heterogeneity using the Cochran's Q test and the I 2 statistic.

Results

Our post-hoc analysis encompassed 3 clinical trials and a total of 835 participants. The mean age of all 835 participants across the three trials was 59.5 years (95% CI: 58.7-60.3). The pooled progression-free survival (PFS)-was estimated at 4.38 (95% CI: -7.58-16.35, P = 0.47), and the pooled objective response rate (ORR) was 7% (95% CI: 2-18%, P = 0.04), with significant heterogeneity observed among the studies.

Discussion

Elacestrant shows promise for improving outcomes in hormone receptor-positive metastatic breast cancer, but further research is needed to confirm its effectiveness. Future studies should include larger sample sizes, comprehensive phase II and III trials, and investigation of elacestrant in combination with other drugs or in preoperative settings.

Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer

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.

Clinico-pathological factors predicting pathological response in early triple-negative breast cancer

Pathological complete response (pCR) after neoadjuvant chemoimmunotherapy (NACi) is associated with improved patient outcomes in early triple-negative breast cancer (TNBC). This study aimed to identify factors associated with pCR after NACi. This cohort included all patients with stage II-III TNBC treated with NACi who underwent surgery at Institut Curie hospitals between 08/2021-06/2023. Among 208 patients, the overall pCR rate was 70% and was similar in ER < 1% (69%) and ER-low TNBC (73%, p = 0.6). In a multivariate model, Ki-67 ≥ 30% (OR 5.19 [1.73-17.3]), centralized TILs ≥ 30% (OR = 3.08 [1.42-7.04]), absence of DCIS at initial biopsy (OR = 2.56 [1.08-6.25]) and germline mutations in homologous recombination genes (OR = 9.50 [2.37-67.7]) remained strong independent predictors of pCR. These findings may guide treatment decisions in patients with TNBC undergoing NACi. Almost all patients with germline mutations in HR genes achieved pCR, supporting de-escalation trials. We suggest that ER-low tumors should be managed as TNBC tumors.

Geometric characteristics of stromal collagen fibres in breast cancer using differential interference contrast microscopy

Breast cancer (BC) is characterised by a high level of heterogeneity, which is influenced by the interaction of neoplastic cells with the tumour microenvironment. The diagnostic and prognostic role of the tumour stroma in BC remains to be defined. Differential interference contrast (DIC) microscopy is a label-free imaging technique well suited to visualise weak optical phase objects such as cells and tissue. This study aims to compare stromal collagen fibre characteristics between in situ and invasive breast tumours using DIC microscopy and investigate the prognostic value of collagen parameters in BC. A tissue microarray was generated from 200 cases, comprising ductal carcinoma in situ (DCIS; n = 100) and invasive tumours (n = 100) with an extra 50 (25 invasive BC and 25 DCIS) cases for validation was utilised. Two sections per case were used: one stained with haematoxylin and eosin (H&E) stain for histological review and one unstained for examination using DIC microscopy. Collagen fibre parameters including orientation angle, fibre alignment, fibre density, fibre width, fibre length and fibre straightness were measured. Collagen fibre density was higher in the stroma of invasive BC (161.68 ± 11.2 fibre/µm2) compared to DCIS (p < 0.0001). The collagen fibres were thinner (13.78 ± 1.08 µm), straighter (0.96 ± 0.006, on a scale of 0-1), more disorganised (95.07° ± 11.39°) and less aligned (0.20 ± 0.09, on a 0-1 scale) in the invasive BC compared to DCIS (all p < 0.0001). A model considering these features was developed that could distinguish between DCIS and invasive tumours with 94% accuracy. There were strong correlations between fibre characteristics and clinicopathological parameters in both groups. A statistically significant association between fibre characteristics and patients' outcomes (breast cancer specific survival, and recurrence free survival) was observed in the invasive group but not in DCIS. Although invasive BC and DCIS were both associated with stromal reaction, the structural features of collagen fibres were significantly different in the two disease stages. Analysis of the stroma fibre characteristics in the preoperative core biopsy specimen may help to differentiate pure DCIS from those associated with invasion.

Mechanistic insights into pachymic acid's action on triple-negative breast Cancer through TOP2A targeting

Triple-negative breast cancer (TNBC) is characterized by the absence of estrogen and progesterone receptors, and lack of human epidermal growth factor receptor 2 (HER2) expression. Traditional Chinese medicine (TCM) has demonstrated promising efficacy in treating TNBC. This study explored the mechanisms of pachymic acid (PA) on TNBC by merging network pharmacology with experimental validation. We acquired Microarray data of TNBC from the Gene Expression Omnibus (GEO). The related targets of PA were predicted and screened using the following 6 databases: Swiss Target Prediction, HERB (Herbal Medicine Database), ETCM (Encyclopedia of Traditional Chinese Medicine), BATMAN (Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine), HIT (Herb Ingredients' Targets Database), and PharmMapper. The STRING interaction network analysis tool was used to create Protein-Protein Interaction (PPI) networks. Enrichment analysis included Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We conducted a pan-cancer analysis, tumor immune microenvironment analysis, and molecular docking. We performed cell experimental, included cytotoxicity assay, apoptosis analysis, proliferation assay, and migration and invasion assays. PA has potential for treating TNBC with the target of TOP2A, and platinum drug resistance possibly serving as the KEGG pathway through which PA exerts its therapeutic effects. PA is involved in processes such as nuclear division, chromosome segregation, mitotic nuclear division, condensed chromosome formation, and protein C-terminus binding. PA probably exert its therapeutic effects through the tumor immune microenvironment, involving elements such as Dendritic cells activated, Eosinophils, Macrophages M0, Macrophages M1, and T cells CD4 memory activated. The therapeutic effects of PA may vary across different subtypes of TNBC such as TNBC-BL1, TNBC-Metaplastic, and TNBC-BL2. This study provides compelling evidence that PA holds significant promise as a therapeutic agent for TNBC, primarily through its action on TOP2A and its influence on the TNBC.

Subtype-specific prognostic impact of Bcl-2 in HER2-positive and HER2-negative breast cancer

Bcl-2, a key regulator of cellular apoptosis, is typically linked to adverse prognosis in solid tumors due to its inhibition of apoptotic cell death and promotion of cellular proliferation, leading to tumor progression. However, studies on Bcl-2 in breast cancer have shown inconsistent results, with some indicating favorable outcomes. This study aims to determine the subtype-specific role of Bcl-2 in breast cancer. Female breast cancer patients who completed primary treatment at Wonju Severance Hospital, Korea, from 2004 to 2018 were included. Clinicopathological characteristics, including Bcl-2 expression, were collected, and patients were classified based on Bcl-2 expression in more than or less than 10% of tumor cells. Kaplan-Meier curves compared recurrence-free interval (RFI) and overall survival (OS). The final cohort of 617 patients, with a mean age of 54.79 ± 11.2 years, showed no overall survival difference by Bcl-2 status (p = 0.616). In HER2-overexpressed patients, high Bcl-2 expression was linked to poor prognosis (p = 0.0021). This trend appeared in ER-positive (p = 0.297) and ER-negative (p = 0.029) subgroups. Conversely, in HER2-negative patients, Bcl-2 overexpression indicated better survival (p = 0.009), consistent in ER-positive (p = 0.259) and ER-negative (p = 0.010) subgroups. Bcl-2's impact on survival varies with HER2 status, showing poor prognosis in HER2-overexpressed and better prognosis in HER2-negative patients.

Molecular heterogeneity and MYC dysregulation in triple-negative breast cancer: genomic advances and therapeutic implications

Triple-negative breast cancer (TNBC) is characterized by a diverse range of molecular features that have been extensively studied. MYC plays a critical role in regulating metabolism, differentiation, proliferation, cell growth, and apoptosis. Dysregulation of MYC is associated with poor prognosis and contributes to the development and progression of breast cancer. A particularly intriguing aspect of TNBC is its association with tumors in BRCA1 mutation carriers, especially in younger women. MYC may also contribute to resistance to adjuvant treatments. For TNBC, targeting MYC-regulated pathways in combination with inhibitors of other carcinogenic pathways offers a promising therapeutic approach. Several signaling pathways regulate TNBC, and targeting these pathways could lead to effective therapeutic strategies for breast cancer. Advances in genomic tools, such as CRISPR-Cas9, next-generation sequencing, and whole-exome sequencing, are revolutionizing breast cancer diagnoses. These technologies have significantly enhanced our understanding of MYC oncogenesis, particularly through CRISPR-Cas9 and NGS. Targeting MYC and its partner MAX could provide valuable insights into TNBC. Moreover, the therapeutic potential of targeting MYC-driven signaling mechanisms and their interactions with other oncogenic pathways, including PI3K/AKT/mTOR and Wnt/β-catenin, is increasingly recognized. Next-generation sequencing and CRISPR-Cas9 represent significant breakthroughs in genomic tools that open new opportunities to explore MYC's role in TNBC and facilitate the development of personalized treatment plans. This review discusses the future clinical applications of personalized treatment strategies for patients with TNBC.

Survival outcomes of neoadjuvant versus adjuvant therapy in patients with T1c, node-negative, human epidermal growth factor receptor 2-positive breast cancer: A Surveillance, Epidemiology, and End Results population-based study

BACKGROUND

Persistent debates exist regarding the superiority of neoadjuvant therapy (NAT) over adjuvant therapy (AT) for patients with T1c, node-negative, human epidermal growth factor receptor 2-positive (HER2+) breast cancer, and relevant guidelines for these patients are lacking.

METHODS

Data on patients with T1cN0M0-stage HER2+ breast cancer who received chemotherapy and surgery were extracted from 2010 to 2020 from the Surveillance, Epidemiology, and End Results database. Propensity score matching (PSM) was used to create well-balanced cohorts for the NAT and AT groups. Kaplan-Meier (KM) analysis and Cox proportional hazards models were used to assess the differences between NAT and AT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). Additionally, logistic regression models were used to explore factors associated with response to NAT.

RESULTS

After PSM, 2140 patient pairs were successfully matched, which achieved a balanced distribution between the NAT and AT groups. KM curves revealed similar OS and BCSS between patients receiving NAT and those undergoing AT. A multivariate Cox model identified achieving pathological complete response (pCR) after NAT, compared with AT, as a protective prognostic factor for OS (hazard ratio, 0.52; 95% CI, 0.35-0.77; p < .001) and BCSS (hazard ratio, 0.60; 95% CI, 0.37-0.98; p = .041). A logistic regression model revealed that White race and hormone receptor-negative status independently predicted pCR.

CONCLUSIONS

For patients with T1cN0M0-stage HER2+ breast cancer, NAT demonstrated comparable OS and BCSS to AT. Patients who achieved pCR after NAT exhibited significantly better survival outcomes compared with those who received AT.

Outcomes of patients treated with chemotherapy for breast cancer during pregnancy compared with nonpregnant breast cancer patients treated with systemic therapy

INTRODUCTION

Prior studies of patients treated for breast cancer during pregnancy (PrBC) report mixed outcomes and are limited by substandard treatment, small cohorts, and short follow-up. This study compared survival outcomes of PrBC patients treated with chemotherapy during pregnancy with nonpregnant patients matched by age, year of diagnosis, stage, and subtype.

METHODS

PrBC patients treated from 1989 to 2022 on prospective institutional protocols were eligible. Disease-free survival (DFS), overall survival (OS), and progression-free survival (PFS) were estimated using the Kaplan-Meier method and multivariable Cox proportional hazards regression.

RESULTS

Among 143 PrBC and 285 nonpregnant patients, median follow-up was 11.4 years. Survival differences were statistically significant, with median DFS and OS not attained for PrBC patients versus 5.6 years (95% confidence interval [CI], 3.6-15.4; p = .0001) and 19.3 years (95% CI, 14.1-not estimated; p = .0262) for nonpregnant patients, respectively. Median PFS was 24.1 years (95% CI, 15.8-not estimated) for PrBC patients versus 8.4 years (95% CI, 6.4-10.9) for the nonpregnant cohort (p = .0008). Study cohort was associated with DFS, PFS, and OS in multivariable analyses, with the nonpregnant cohort having increased risks of disease recurrence (hazard ratio [HR], 1.91; 95% CI, 1.33-2.76; p = .0005) and disease progression or death (HR, 1.68; 95% CI, 1.19-2.39; p = .0035), and shorter OS (HR, 1.52; 95% CI, 1.01-2.29; p = .0442).

CONCLUSION

These data suggest that PrBC patients treated with chemotherapy during pregnancy have at least comparable, if not superior, outcomes than nonpregnant patients with similar age, cancer stage, and subtype. Analyses excluding patients with postpartum breast cancer were unable to be performed and are a priority for future confirmatory studies.

Impacts of Tumor Stage at Diagnosis and Adjuvant Therapy on Long-Term Survival Outcomes in Patients With Triple-Negative Breast Cancer Achieving Pathologic Complete Response After Neoadjuvant Chemotherapy

BACKGROUND

It remains unknown whether the tumor stage at initial diagnosis and adjuvant treatments had any impacts on the long-term survival outcomes of patients with triple-negative breast cancer (TNBC) achieving pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT).

METHODS

Clinical stage II-III patients with TNBC who achieved pCR after NACT were identified from the Surveillance, Epidemiology, and End Results (SEER) program (SEER cohort) and the National Clinical Research Center for Cancer (Tianjin) in China (TMUCIH cohort). Survival analyses were conducted based on tumor stages and the types of adjuvant treatment received by the patients. The outcomes of interest were overall survival (OS) and breast cancer-specific survival (BCSS).

RESULTS

The TMUCIH cohort comprised 178 patients with a median follow-up of 55.5 months. Two and 3 patients experienced BCSS and OS events, respectively. The SEER cohort included 1218 patients with a median follow-up of 65.5 months, where 53 and 78 patients experienced BCSS and OS events, respectively. Patients diagnosed with stage III disease had significantly higher hazards of death compared to stage II disease (OS: hazard ratio [HR], 3.34; 95% confidence interval [CI], 1.84-6.07; P < .001; BCSS: HR, 2.86; 95% CI, 1.38-5.92; P < .001). Adjuvant systemic and radiation therapy did not confer additional benefits to OS and BCSS.

CONCLUSION

Tumor stage at initial diagnosis remains an independent predictor of long-term survival outcomes in patients with TNBC achieving pCR after NACT. Postoperative adjuvant chemotherapy and radiation therapy do not appear to provide additional benefit to their long-term prognosis.

Discoidin Domain Receptor 2 Contributes to Breast Cancer Progression and Chemoresistance by Interacting with Collagen Type I

Background: Chemoresistance is an important issue to be solved in breast cancer. It is well known that the content and morphology of collagens in tumor tissues are drastically altered following chemotherapy, and discoidin domain receptor 2 (DDR2) is a unique type of receptor tyrosine kinase (RTK). This RTK is activated by collagens, playing important roles in human malignancies. However, the contribution to the chemoresistance of DDR2 in terms of the association with collagens remains largely unclear in breast cancer. Methods: We immunolocalized DDR2 and collagen type I in 224 breast cancer tissues and subsequently conducted in vitro studies to confirm the role of DDR2 in breast cancer chemoresistance using chemosensitive and chemoresistant cell lines. Results: DDR2 immunoreactivity was positively correlated with aggressive behaviors of breast cancer and was significantly associated with an increased risk of recurrence, especially in those who received chemotherapy. Moreover, in vitro experiments demonstrated that DDR2 promoted the proliferative activity of breast cancer cells, and cell viability after epirubicin treatment was significantly maintained by DDR2 in a collagen I-dependent manner. Conclusions: These data suggested that DDR2 could be a poor prognostic factor associated with cell proliferation and chemotherapy resistance in human breast cancer.

Cold ischemia time and formalin fixation time in endometrial cancer: Should breast cancer guidelines for preanalytical variables be applied to hysterectomy specimens?

OBJECTIVES

The American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) recommend cold ischemia time (cIT) be <60 min, and formalin fixation time (FFT) 6-72 h, to optimize immunohistochemistry (IHC) based on breast cancer data. We assessed whether cIT and FFT impact IHC in endometrial cancer (EC), and determined which factors affect cIT and FFT.

METHODS

Surgical EC cases from 2019 to 2023 were reviewed. cIT was calculated by subtracting time of tissue devascularization intra-operatively from time the specimen was placed in formalin. Demographics, clinicopathologic and peri-operative factors, and IHC for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and mismatch repair (MMR) proteins were compared between patients with cIT <60 min versus ≥60 min (prolonged), and compliant FFT (6-72 h) versus non-compliant FFT (<6 or > 72 h). Categorical variables were compared using χ2 tests.

RESULTS

941 patients were included in the analysis. Median cIT was 33 min. Prolonged cIT occurred in 95 (10 %) cases. African American/Black race (p < 0.001), advanced stage (p < 0.001), mini-laparotomy (p < 0.001), performance of surgical procedures beyond standard EC staging (p < 0.001), longer surgical length (p < 0.001), and increased uterine weight (p < 0.001) were independently associated with prolonged cIT. There were no significant differences in ER, PR, HER2, or MMR protein expression based on cIT or FFT.

CONCLUSION

Prolonged cIT was not associated with differences in biomarker expression via IHC at time of surgical staging for EC. Despite variability in cIT, which is largely due to non-modifiable factors, tumor molecular features remain consistent and can reliably be utilized for prognostic and therapeutic decision-making.

Diagnostic Accuracy and Clinical Utility of Fine-Needle Aspiration in Breast Lesions: A Correlation with Surgical Pathology

INTRODUCTION

Fine-needle aspiration (FNA) is a valuable diagnostic tool for evaluating breast lesions, yet its use is less frequent compared to core needle biopsies in high-resource settings. This study aimed to assess the diagnostic performance and clinical utility of FNA in correlation with surgical pathology outcomes.

METHODS

We performed a 3-year retrospective search (2021-2023) using our institutional database to identify cases of breast mass FNAs performed by interventional radiologists under ultrasound guidance. We retrieved and re-evaluated all glass slides from the archive. Additionally, we reviewed the cytopathology reports and correlated the cytologic diagnoses with concurrent or subsequent surgical pathology results.

RESULTS

A total of 65 breast FNA cases from patients were reviewed. The diagnostic outcomes were 55% negative for malignancy, 23% insufficient for diagnosis, 11% atypical, 8% suspicious for malignancy, and 3% positive for malignancy. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of FNA for detecting malignancy were 76%, 96%, 93%, and 85%, respectively. One false positive case, categorized as atypical due to degenerative changes, was later confirmed as benign apocrine metaplasia. Three false-negative cases, initially categorized as non-diagnostic, were later diagnosed as invasive ductal carcinoma, Hodgkin lymphoma, and papillary carcinoma. An additional false-negative case, categorized under negative for malignancy, was later diagnosed as invasive ductal carcinoma.

CONCLUSION

Breast FNAs, while less frequently performed than core needle biopsies, provide significant diagnostic insights, particularly for cystic lesions. The study demonstrates high specificity and PPV for FNA in detecting malignancy, underscoring its value as a diagnostic tool when integrated with imaging and clinical assessment. These findings support the continued use of FNA in the diagnostic evaluation of breast lesions.

Current Therapeutic Opportunities for Estrogen Receptor Mutant Breast Cancer

Estrogen receptor α (ERα) drives two out of three breast cancers and therefore ERα is a major therapeutic target for ER-positive breast cancer patients. Drugs that inhibit ERα activity or block estrogen synthesis in the body are currently being used in the clinic to treat ER-positive breast cancer and have been quite successful in controlling breast cancer progression for the majority of patients. However, ER-positive breast cancer often becomes resistant to these endocrine therapies, leading to endocrine-resistant metastatic breast cancer, a very aggressive cancer that leads to death. Recent large-scale genomic studies have revealed a series of activating somatic mutations in the ERα gene (ESR1) in endocrine-resistant metastatic breast cancer patients. Of these, Y537S and D538G mutations are found at a much higher rate in patients with metastatic breast cancer. Remarkably, these mutations produce an ERα with much higher transcriptional activity than wild type in the absence of estradiol, and traditional endocrine therapy has poor efficacy against ER mutants. Therefore, the development of new drugs that target ER mutants is an unmet clinical need for endocrine-resistant metastatic breast cancer. This review summarizes the recent preclinical and clinical trials targeting estrogen receptor mutant breast cancer.

Neuroanatomical location of lung cancer brain metastases in 234 patients with a focus on cancer subtyping and biomarkers

Brain metastases are frequent in neuropathology practices; however, the literature on their distribution is frequently derived from imaging studies. This work examined metastases of lung cancer to the brain through the lens of pathology specimens. All brain surgical pathology cases accessioned from 2011-2020 were retrieved from a regional laboratory. Specimens were classified by neuroanatomical location, diagnostic category, and diagnosis with a hierarchical free text string-matching algorithm. All reports classified as probable metastasis per algorithm were reviewed by a pathologist. Lung biomarkers and selected immunostains were retrieved with text parsing and reviewed. Among 4,625 cases of brain surgical resection specimens, 854 were classified as probable metastasis by the algorithm. On report review, 538/854 cases were confirmed as metastasis with a known primary site. The 538 cases were from 511 patients and 234/511 patients had lung primaries. Small cell lung cancer lesions were most frequently found in the cerebellum (17/30). Lesions from lung adenocarcinoma (59/164) and non-small cell carcinoma-not otherwise specified (NSCLC-NOS) (15/34) were most commonly found in the frontal lobe. Squamous cell carcinoma lesions were most commonly found in the frontal and occipital lobes (8/27). 72/234 cases were reported as NSCLC-NOS and could be further subclassified using immunostaining (41/72). Lung biomarker data were retrieved in ~38% of cases. PD-L1 positivity was dependent on neuroanatomical distribution (p = 0.04); other examined biomarkers were not. The distribution of lung tumours metastatic to the brain is dependent on the lung cancer subtype (p<0.001). The reporting of histologic subtype could be further optimized in the local environment.

Are All Prognostic Stage IB Breast Cancers Equivalent?

Background/Objectives: The 8th edition of the American Joint Committee on Cancer integrates histology and biomarker status with anatomic extent in breast cancer (BC) pathologic prognostic staging (PPS). However, PPS IB includes anatomic locally advanced hormone-receptor-positive/HER2-negative (LA-HR+/HER2-) and early-stage triple-negative BC (ES-TNBC). Previous research shows that increased nodal involvement is a critical predictor of worse prognosis, raising questions about whether biological subtype or anatomic stage has a greater influence on outcomes in these discordant cases. We hypothesized that overall survival (OS) remains worse for LA-HR+/HER2- BC compared to ES-TNBC, despite both being classified as PPS IB. Methods: Using the National Cancer Database, we identified patients with LA-HR+/HER2- BC (pT3N1 or pT1-3N2, grade 1-2) and ES-TNBC (T1N0, grade 2-3) treated between 2004 and 2017. Patients without complete primary tumor stage, biomarker status, grade, TNM staging, or treated with neoadjuvant therapy were excluded. The primary endpoint was OS. Multivariable Cox regression evaluated OS between LA-HR+/HER2- BC and ES-TNBC. Results: Among 45,818 patients (17,359 LA-HR+/HER2- BC and 28,459 ES-TNBC), LA-HR+/HER2- BC had significantly worse 6-year OS (86.1% vs. 90.4%; HR = 1.63; p < 0.0001). Among patients receiving appropriate therapies, patients with LA-HR+/HER2- BC had 35% relatively higher risk of death (HR = 1.35; 1.24-1.48; p < 0.0001). These results highlight that LA-HR+/HER2- breast cancer has worse survival compared to ES-TNBC, despite both being classified as PPS IB and receiving all appropriate treatments. Conclusions: Anatomic disease extent remains an important factor in patients with discordant AS and PPS. Future iterations of PPS should re-classify LA-HR+/HER2- breast cancer from PPS IB to ensure more accurate prognostic and survival information.

Financial Difficulty Over Time in Young Adults With Breast Cancer

IMPORTANCE

Young adults aged 18 to 39 years represent the minority of breast cancer diagnoses but are particularly vulnerable to financial hardship. Factors contributing to sustained financial hardship are unknown.

OBJECTIVES

To identify financial hardship patterns over time and characterize factors associated with discrete trajectories; it was hypothesized that treatment-related arm morbidity, a key source of expense, would be associated with long-term financial difficulty.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included US young adults aged 40 years or younger treated between 2006 and 2016. Eligible patients were treated for stage 0 to stage III breast cancer at institutions participating in the Young Women's Breast Cancer Study, which included a specialized cancer institute and 12 other academic and community hospitals. Patients who responded at baseline and returned a 1-year survey were included in analysis. Data were analyzed in March 2024.

MAIN OUTCOMES AND MEASURES

Trajectory modeling classified patterns of financial difficulty from baseline through 10 years postdiagnosis using the Cancer Rehabilitation Evaluation System (CARES) scale. Multinomial regression examined characteristics, including treatment-related arm morbidity, associated with each trajectory.

RESULTS

A total 1008 patients were included (median [IQR] age at diagnosis, 36 [33-39] years; 60 Asian [6.0%], 35 Black [3.5%], 47 Hispanic [4.7%], 884 White [87.7%]); 840 patients were college graduates (83.3%), 764 were partnered at baseline (75.8%), 649 were nulliparous (64.4%), and 908 were without comorbidities at enrollment (90.1%). Patients' tumors were primarily stage I-II (778 [77.2%]), estrogen receptor/progesterone receptor-positive (754 [74.8%]), and ERBB2-negative (formerly HER2) (686 [68.1%]). Patients were more frequently treated with mastectomy than breast conservation (771 [76.5%] vs 297 [29.5%]; P < .001). A majority of patients received radiation therapy (627 [62.2%]), chemotherapy (760 [75.4%]), and endocrine therapy (610 [60.6%]). A total of 727 patients (72.1%) reported arm symptoms within 2 years of surgery. Three distinct trajectories of experiences with finances emerged: 551 patients (54.7%) had low financial difficulty (trajectory 1), 293 (29.1%) had mild difficulty that improved (trajectory 2), and 164 (16.3%) had moderate to severe difficulty peaking several years after diagnosis before improving (trajectory 3). Hispanic ethnicity (OR, 3.71; 95% CI, 1.47-9.36), unemployment at baseline and 1 year (OR, 2.66; 95% CI, 1.63-4.33), and arm symptoms (OR, 1.77; 95% CI, 1.06-2.96) were associated with increased odds of experiencing trajectory 3. Having a college degree (OR, 0.20; 95% CI, 0.12-0.34) or being partnered (OR, 0.24; 95% CI, 0.15-0.38) were associated with increased odds of experiencing trajectory 1.

CONCLUSION

In this cohort study of young adults with breast cancer, we identified a subset of patients who experienced a high degree of financial difficulty persisting into early survivorship. Targeted interventions to mitigate financial toxicity-modifiable factors that include support for the employability or return to work support for those experiencing arm symptoms after treatment-are needed.

The influence of fixing condition on myoglobin stainability of striated muscle as a tool for forensic diagnosis

It is reported that immunostaining of Myoglobin (Mb) is useful for forensic diagnosis. In this study, we investigated the condition of fixation of striated muscle in 10 % neutral-buffered formalin to obtain appropriate stationarity of Mb in immunostaining. Firstly, criteria for staining intensity and definition of the stainability of examined were determined for sheep muscle tissue. Sheep myocardial tissue was fixed using 10 % neutral-buffered formalin under the 21 different conditions based on combinations of the following: three ratios of volume of formalin (mL) to weight of myocardium (g) (RFM) of 1, 4 or 9, 7 durations of fixation (DF) of 0.5, 3 or 6 h, and 1, 2, 5 or 7 days. Secondly, detection of Mb diffused form skeletal muscle from autopsy cases into formalin during fixation were confirmed by ELISA. Finally, the evaluation of stainability of Mb of striated muscle in routine autopsy examinations was confirmed using sheep staining intensity standards. From this experimental investigation, it has been demonstrated that the most suitable formalin fixation condition for using Mb staining in forensic diagnosis is RFM4 with a fixation time of at least DF 3 h up to 1 day. It was evident that staining intensity decreases with fixation durations exceeding 2 days, irrespective of the RFM. Thus, the fixation time was deemed the most influential factor affecting the staining properties of Mb staining in skeletal muscle tissue. When conducting Mb staining using striated muscle as an evaluation sample, particular attention should be paid to the fixation time.

Breast cancer molecular subtype classification according to immunohistochemistry markers and its association with pathological characteristics among women attending tertiary hospitals in Tanzania

Background

Breast cancer immunohistochemistry is a biological characteristic of the tumour which has a role to diagnose molecular subtype, prognosticate and guide treatment and is categorised into 4 subtypes. Data in Tanzania was lacking and was based off data extrapolated from studies in Western Africa thus hypothesizing that women of African ancestry predominately develop Triple Negative Breast Cancer (TNBC).

Methods

A retrospective cross-sectional study was carried out at two tertiary referral hospitals on participants who were recruited from the cancer registries from 2015 to 2022. Prevalence of each molecular subtype was determined and association between molecular subtype to demographic and pathological characteristics were evaluated. Predictors of molecular subtypes was then determined using logistic regression.

Results

Total number of participants were 1214, median age was 50 (IQR: 41-61), median tumor size was 5 cm (IQR: 4-7) with lymph node positivity in 73.7 %. Immunohistochemistry studies showed estrogen, progesterone and Human Epidermal Growth Factor Receptor 2 (HER2) receptor positivity in 54.4 %, 34.4 % and 27.8 % of cases respectively. Molecular subtype classification prevalence for Luminal A was 21.17 % (95 % CI: 18.87-23.47), for Luminal B 35.75 % (95 % CI: 33.05-38.45), for HER2 enriched 11.86 % (95 % CI: 10.04-13.68) and for TNBC 31.22 % (95 % CI: 28.61-33.83). Significant association was seen between molecular subtype with age, tumor size, tumor grade and lymph node involvement. Predictors of Luminal tumors were larger tumor size (aOR 1.217, 95 % CI: 1.149-1.291) no lymph node involvement (aOR 0.429, 95 % CI: 0.313-0.589) while an advanced tumor grade reduced likelihood (aOR 0.041, 95 % CI: 0.011-0.019).

Conclusion

In Tanzania Luminal B was most predominant subtype presenting at an earlier age and associated with more favorable pathological characteristics.

Bi-level Graph Learning Unveils Prognosis-Relevant Tumor Microenvironment Patterns in Breast Multiplexed Digital Pathology

The tumor microenvironment is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. There have been increasing efforts dedicated to characterizing this complex and heterogeneous environment, including developing potential prognostic tools by leveraging modern deep learning methods. However, the identification of generalizable data-driven biomarkers has been limited, in part due to the inability to interpret the complex, black-box predictions made by these models. In this study, we introduce a data-driven yet interpretable approach for identifying patterns of cell organizations in the tumor microenvironment that are associated with patient prognoses. Our methodology relies on the construction of a bi-level graph model: (i) a cellular graph, which models the intricate tumor microenvironment, and (ii) a population graph that captures inter-patient similarities, given their respective cellular graphs, by means of a soft Weisfeiler-Lehman subtree kernel. This systematic integration of information across different scales enables us to identify patient subgroups exhibiting unique prognoses while unveiling tumor microenvironment patterns that characterize them. We demonstrate our approach in a cohort of breast cancer patients and show that the identified tumor microenvironment patterns result in a risk stratification system that provides new complementary information with respect to standard stratification systems. Our results, which are validated in two independent cohorts, allow for new insights into the prognostic implications of the breast tumor microenvironment. This methodology could be applied to other cancer types more generally, providing insights into the cellular patterns of organization associated with different outcomes.

Optimized biomarker evaluation and molecular testing in the era of breast cancer precision medicine

Ground breaking advances in medicine, driven in part by major technologic developments in molecular biology have led us to a new model for cancer care that has been termed personalized, or precision medicine. Precision medicine is a model for making medical decisions that employs an innovative clinical approach and advanced tumor testing methods that are tailored to understanding an individual patient's tumor biology and the molecular drivers of their disease. This medical model includes a combination of diagnostic testing and specific treatment options that can be offered to patients at presentation and in theory throughout the course of their disease as new mutations arise with the development of disease recurrence. Although the precision medicine model offers incredible potential to transform cancer care, these advances are only meaningful when they reach the correct patients. The evolving paradigm of precision medicine is changing the practice of pathology, and the pathology community needs to be mindful of these changes because every tissue specimen represents a patient's life, and those patients are depending on the pathology community to handle their tissue correctly. The diagnostic tests performed in the pathology laboratory for precision medicine are increasingly complex, and pathologists along with the entire laboratory and clinical communities need to take steps to ensure that the right diagnosis is given to the right patient to inform the right treatment options, at the right time, along every step of the continuum of care for cancer patients. While hormone receptors and human epidermal growth factor receptor 2 (HER2) overexpression and/or amplification have been the mainstay for risk-stratification, and treatment decision making in breast cancer since the early 2000's, the seminal work on gene expression by Perou and colleagues in the early 2000's opened the door for molecular testing in the prognostic and predictive assessment of breast cancer. Molecular testing is now part of the standard of care in the precision medicine model for breast cancer care. In this article, the reader will gain a better understanding of how the lack of standardization of pre-analytic factors has the potential to negatively impact the quality of the tissue specimen for downstream biomarker and molecular testing, which ultimately can negatively affect patient care. The reader will also gain insight into the current climate surrounding molecular testing in breast cancer.

Establishment of prognostic model for invasive ductal carcinoma with distant metastasis within the triple-negative breast cancer: a SEER population-based study

Triple-negative breast cancer (TNBC) is a complex and diverse group of malignancies. Invasive ductal carcinoma (IDC) is the predominant pathological subtype and is closely linked to the ominous potential for distant metastasis, a pivotal factor that significantly influences patient outcomes. In light of these considerations, the present study was conceived with the objective of developing a nomogram model. This model was designed to predict the prognosis observed in IDC with distant metastasis in TNBC. This was a retrospective study based on the SEER database. Data of 9739 IDC-TNBC patients diagnosed from 2010 to 2020 were included in our study. Independent risk factors were screened by univariate and multivariate Cox regression analyses successively, which were used to develop a nomogram model predicting for prognosis. Cox multivariable analysis showed statistical significance in bone metastasis, liver metastasis, surgery, and chemotherapy. Incorporating statistically significant variables, as well as clinically significant age, lung metastasis, and brain metastasis into the construction of the prediction model, the C-indexes of the training group and validation group were 0.702 (0.663-0.741) and 0.667 (0.600-0.734), respectively, while the calibration curves were all close to the ideal 45° reference line, and decision curve analysis curves show excellent net benefit in the predictive model. The prognostic prediction model developed in this study demonstrated enhanced predictive accuracy, enabling a more precise evaluation of mortality risks associated with IDC with distant metastasis in TNBC.

Glucocorticoid receptors orchestrate a convergence of host and cellular stress signals in triple negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks expression of the nuclear steroid receptors that bind estrogens (ER) and progestogens (PRs) and does not exhibit HER2 (Human epidermal growth factor 2) receptor overexpression. Even in the face of initially effective chemotherapies, TNBC patients often relapse. One primary cause for therapy-resistant tumor progression is the activation of cellular stress signaling pathways. The glucocorticoid receptor (GR), a corticosteroid-activated transcription factor most closely related to PR, is a mediator of both endocrine/host stress and local tumor microenvironment (TME)-derived and cellular stress responses. Interestingly, GR expression is associated with a good prognosis in ER+ breast cancer but predicts poor prognosis in TNBC. Classically, GR's transcriptional activity is regulated by circulating glucocorticoids. Additionally, GR is regulated by ligand-independent signaling events. Notably, the stress-activated protein kinase, p38 MAP kinase, phosphorylates GR at serine 134 (Ser134) in response to TME-derived growth factors and cytokines, including HGF and TGFβ1. Phospho-Ser134-GR (p-Ser134-GR) associates with cytoplasmic and nuclear signaling molecules, including 14-3-3ζ, aryl hydrocarbon receptors (AhR), and hypoxia-inducible factors (HIFs). Phospho-GR/HIF-containing transcriptional complexes upregulate gene sets whose protein products include the components of inducible oncogenic signaling pathways (PTK6) that further promote cancer cell survival, chemoresistance, altered metabolism, and migratory/invasive behavior in TNBC. Recent studies have implicated liganded p-Ser134-GR (p-GR) in dexamethasone-mediated upregulation of genes related to TNBC cell motility and dysregulated metabolism. Herein, we review the tumor-promoting roles of GR and discuss how both ligand-dependent and ligand-independent/stress signaling-driven inputs to p-GR converge to orchestrate metastatic TNBC progression.

EZH2 mutation is associated with the development of visceral metastasis by enhancing proliferation and invasion and inhibiting apoptosis in breast cancer cells

BACKGROUND

The prognosis of breast cancer patients with visceral metastasis (VM) is significantly worse than that of patients without VM. We aimed to evaluate EZH2 (enhancer of zeste homolog 2) mutation as a biomarker associated with VM.

METHODS

Data from forty-nine patients with metastatic breast cancer (MBC) pathologically confirmed at our hospital between March 2016 and September 2018 were collected. Metastatic tissue samples were obtained via ultrasound-guided needle biopsy, and paired peripheral blood samples were also collected. Tissue and blood samples were subjected to targeted next-generation sequencing via a 247-gene panel. Stably transfected MDA-MB-231 cells expressing wild-type EZH2 (EZH2WT) or a mutant form of EZH2 (EZH2K515R) were generated. Cell proliferation, colony formation ability, migration and invasion abilities and apoptosis were assessed using CCK-8 assays, plate colony formation assays, Transwell chamber assays and flow cytometry.

RESULTS

The incidence of EZH2 mutations in the VM subgroup was greater than that in the non-VM subgroup in the entire cohort (n = 49, 42.3% vs. 13.0%, p = 0.024) and in the triple-negative breast cancer (TNBC) subgroup (n = 20, 50.0% vs. 10.0%, p = 0.05). Patients carrying EZH2 mutations had a significantly greater risk of developing VM than did those in the non-EZH2 mutation group in the entire cohort (HR 2.9) and in the TNBC subgroup (HR 6.45). Multivariate analysis revealed that EZH2 mutation was an independent prognostic factor for VM (HR 2.99, p = 0.009) in the entire cohort and in the TNBC subgroup (HR 10.1, p = 0.006). Data from cBioPortal also showed that patients with EZH2 mutations had a significantly greater risk of developing VM (HR 3.1), and the time to develop VM was significantly earlier in the EZH2 mutation group (31.5 months vs. 109.7 months, p = 0.008). Multivariate analysis revealed that EZH2 mutation (HR 2.73, p = 0.026) was an independent factor for VM after breast cancer surgery. There was no correlation between EZH2 mutations and BRCA1/2 mutations. Most of the patients (81.8%) in our cohort who developed VM carried the "c.1544A > G (p.K515R)" mutation. Compared with EZH2WT MDA-MB-231 cells, EZH2K515R MDA-MB-231 cells had greater colony formation rates (p < 0.01), greater migration and invasion rates (p < 0.001), and lower apoptosis rates (p < 0.01). The proportion of S + G2/M phase cells in the EZH2K515R group was significantly greater than that in the EZH2WT group.

CONCLUSIONS

EZH2 mutation is associated with VM development in breast cancer patients. The EZH2K515R mutation leads to VM and a poor prognosis by enhancing proliferation and invasion and inhibiting apoptosis in breast cancer cells.

External Quality Assurance Helps Improve Infrastructure for Testing Breast Biomarkers Across a Lower- and Middle-Income Country: Our Experience With Breast Biomarker Testing in the National Cancer Grid External Quality Assurance System in India

CONTEXT.—

Biomarkers in breast cancer need strict monitoring given their role in patient management.

OBJECTIVE.—

To study the impact that regular participation in the National Cancer Grid (NCG) external quality assurance (EQA) system has on concordance rates for biomarkers in breast carcinoma.

DESIGN.—

Tissue microarrays (TMAs) containing breast carcinomas were circulated to participating laboratories that performed immunohistochemistry for breast biomarkers. The returned TMAs were then assessed for test concordance.

RESULTS.—

A total of 105 laboratories participated in the estrogen receptor (ER) and progesterone receptor (PR) EQA system cycles, and 99 centers participated in the human epidermal growth factor 2 (HER2) EQA system. In the ER EQA in the first cycle only 1 laboratory had a 100% concordance rate, which improved to 59 of 77 (76.6%) and 85 of 97 (87.6%) in the fourth and fifth cycles, respectively. In the PR EQA the 100% pass rate jumped from zero to 52 of 76 (68.4%) in the fourth cycle and 86 of 97 (88.6%) in the last cycle. For HER2 EQA, the 100% pass rates were seen in 7 of 23 laboratories (30.4%) in the first cycle, 49 of 78 laboratories (62.8%) in the fourth cycle, and 48 of 94 laboratories (51.1%) in fifth cycle of EQA. Centers that participated in the NCG EQA system for a longer period often changed testing methodology, with consequent improvement in their laboratory concordance rates. An increasing trend for the use of automated platforms and of the US Food and Drug Administration-approved antibody for HER2 testing was observed.

CONCLUSIONS.—

Our experience demonstrates that laboratory performance improves with participation in an EQA system even in less perfect settings, and this drives the placement of more proficient practices across the country.

Dataset for reporting of the invasive carcinoma of the breast: recommendations from the International Collaboration on Cancer Reporting (ICCR)

BACKGROUND AND OBJECTIVES

Current national or regional guidelines for the pathology reporting on invasive breast cancer differ in certain aspects, resulting in divergent reporting practice and a lack of comparability of data. Here we report on a new international dataset for the pathology reporting of resection specimens with invasive cancer of the breast. The dataset was produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organizations.

METHODS AND RESULTS

The established ICCR process for dataset development was followed. An international expert panel consisting of breast pathologists, a surgeon, and an oncologist prepared a draft set of core and noncore data items based on a critical review and discussion of current evidence. Commentary was provided for each data item to explain the rationale for selecting it as a core or noncore element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the document was finalized and ratified, and the dataset, which includes a synoptic reporting guide, was published on the ICCR website.

CONCLUSIONS

This first international dataset for invasive cancer of the breast is intended to promote high-quality, standardized pathology reporting. Its widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will help to improve the management of invasive breast cancer patients.

A model combining BI-RADS® descriptors from pre-treatment B-mode breast ultrasound with clinicopathological tumor features shows promise in the prediction of residual disease after neoadjuvant chemotherapy

PURPOSE

To create a simple model using standard BI-RADS® descriptors from pre-treatment B-mode ultrasound (US) combined with clinicopathological tumor features, and to assess the potential of the model to predict the presence of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

METHOD

245 female BC patients receiving NAC between January 2017 and December 2019 were included in this retrospective study. Two breast imaging fellows independently evaluated representative B-mode tumor images from baseline US. Additional clinicopathological tumor features were retrieved. The dataset was split into 170 training and 83 validation cases. Logistic regression was used in the training set to identify independent predictors of residual disease post NAC and to create a model, whose performance was evaluated by ROC curve analysis in the validation set. The reference standard was postoperative histology to determine the absence (pathological complete response, pCR) or presence (non-pCR) of residual invasive tumor in the breast or axillary lymph nodes.

RESULTS

100 patients (40.8%) achieved pCR. Logistic regression demonstrated that tumor size, microlobulated margin, spiculated margin, the presence of calcifications, the presence of edema, HER2-positive molecular subtype, and triple-negative molecular subtype were independent predictors of residual disease. A model using these parameters demonstrated an area under the ROC curve of 0.873 in the training and 0.720 in the validation set for the prediction of residual tumor post NAC.

CONCLUSIONS

A simple model combining standard BI-RADS® descriptors from pre-treatment B-mode breast US with clinicopathological tumor features predicts the presence of residual disease after NAC.

Alteration of HER2 Status During Breast Cancer Progression: A Clinicopathological Analysis Focusing on HER2-Low Status

Recent studies have shown that novel antibody-drug conjugates (ADCs) can improve clinical outcomes in patients with HER2-low breast cancers. This study aimed to investigate alteration of HER2 status during breast cancer progression with an emphasis on HER2-low status. Using 386 paired samples of primary and recurrent breast cancers, HER2 discordance rate between primary and matched recurrent samples, the relationships between HER2 discordance and clinicopathological characteristics and clinical outcomes of the patients were analyzed. HER2 discordance rate between primary breast cancer and first recurrence was 25.9% (κ = 0.586) with mostly zero-to-low (10.6%) or low-to-zero (9.3%) conversion. There was no significant difference in the discordant rates according to type or location of the recurrence. Of 70 cases with a second recurrence, HER2 discordance rate between the primary tumor and the second recurrence was 27.1% (κ = 0.554). HER2 discordance was associated with lower HER2 level, lymphovascular invasion, and progesterone receptor positivity of the primary tumor. In further analyses, HER2-zero-to-low conversion was associated with lymph node metastasis and hormone receptor (HR) positivity, whereas HER2-low-to-zero conversion was associated with HR negativity and triple-negative subtype. In survival analyses, HER2 discordance was associated with decreased overall survival of patients in the HR-positive group but not in the HR-negative group. Furthermore, patients with HER2-low-to-zero converted tumors showed worse overall survival compared with those with HER2-low concordant tumors. In conclusion, HER2 status changes during breast cancer progression in significant proportions, mostly between zero and low status. As HER2 instability increases during progression and affects clinical outcome, HER2 status needs to be reevaluated in recurrent settings.

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study

RATIONALE AND OBJECTIVES

This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer (BC) patients who underwent total mastectomy (TM) and had 1-2 positive sentinel lymph nodes (SLNs).

MATERIALS AND METHODS

In total, 494 patients were retrospectively enrolled from two hospitals, and were divided into the training (n = 286), internal validation (n = 122), and external validation (n = 86) cohorts. Features were extracted from DCE-MRI images for each patient and screened. Six ML classifies were trained and the best classifier was evaluated to calculate radiomics (Rad)-scores. A combined model was developed based on Rad-scores and clinical risk factors, then the calibration, discrimination, reclassification, and clinical usefulness were evaluated.

RESULTS

14 radiomics features were ultimately selected. The random forest (RF) classifier showed the best performance, with the highest average area under the curve (AUC) of 0.833 in the validation cohorts. The combined model incorporating RF-based Rad-scores, tumor size, lymphovascular invasion, and proportion of positive SLNs resulted in the best discrimination ability, with AUCs of 0.903, 0.890, and 0.836 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the combined model significantly improved the classification accuracy and clinical benefit for NSLN metastasis prediction.

CONCLUSION

A RF-based combined model using DCE-MRI images exhibited a promising performance for predicting NSLN metastasis in Chinese BC patients who underwent TM and had 1-2 positive SLNs, thereby aiding in individualized clinical treatment decisions.

Comprehensive understanding of the role of GPER in estrogen receptor-alpha negative breast cancer

G protein-coupled estrogen receptor (GPER) plays a prominent role in facilitating the rapid, non-genomic signaling of estrogens in breast cancer cells. Herein, a comprehensive overview of the role of GPER in ER-ɑ-negative breast cancer is provided. Activation of GPER affected proliferation, metastasis and epithelial mesenchymal transition in ER-ɑ negative breast cancer cells. Clinical studies have demonstrated that GPER positivity was strongly correlated with larger tumor size and advanced clinical stage, suggesting that GPER/ERK signaling may play a role in promoting tumor progression. Strong evidence existed that environmental contaminants like bisphenol A have a carcinogenic potential mediated by GPER activation. The complexity of the cross talk between GPER and other receptors including ER-β, ER-α36, Estrogen-related receptor α (ERRα) and androgen receptor has been discussed. The potential utility of small molecules and phytoestrogens targeting GPER, adds valuable insights into its therapeutic potential. This review holds promises in advancing our understanding of GPER role in ER-ɑ-negative breast cancer. Overall, the consequences of GPER activation are still an area of active research and the implication are not entirely clear.

Combination of DCE-MRI and NME-DWI via Deep Neural Network for Predicting Breast Cancer Molecular Subtypes

BACKGROUND

To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of breast cancer molecular subtypes compared to either imaging technique used alone.

PATIENTS AND METHODS

This prospective study examined 480 breast cancers in 475 patients undergoing DCE-MRI and NME-DWI at 3.0 T. Breast cancers were classified as follows: human epidermal growth factor receptor 2 enriched (HER2-enriched), luminal A, luminal B (HER2-), luminal B (HER2+), and triple-negative subtypes. A total of 20% cases were withheld as an independent test dataset, and the remaining cases were used to train DNN with an 80% to 20% training-validation split and 5-fold cross-validation. The diagnostic accuracies of DNN in 5-way subtype classification between the DCE-MRI, NME-DWI, and their combined multiparametric-MRI datasets were compared using analysis of variance with least significant difference posthoc test. Areas under the receiver-operating characteristic curves were calculated to assess the performances of DNN in binary subtype classification between the 3 datasets.

RESULTS

The 5-way classification accuracies of DNN on both DCE-MRI (0.71) and NME-DWI (0.64) were significantly lower (P < .05) than on multiparametric-MRI (0.76), while on DCE-MRI was significantly higher (P < .05) than on NME-DWI. The comparative results of binary classification between the 3 datasets were consistent with the 5-way classification.

CONCLUSION

The combination of DCE-MRI and NME-DWI via DNN achieved a significant improvement in breast cancer molecular subtype prediction compared to either imaging technique used alone. Additionally, DCE-MRI outperformed NME-DWI in differentiating subtypes.

Construction and validation of a nomogram prediction model for axillary lymph node metastasis of cT1 invasive breast cancer

OBJECTIVE

Based on the ultrasonic characteristics of the breast mass and axillary lymph nodes as well as the clinicopathological information, a model was developed for predicting axillary lymph node metastasis in cT1 breast cancer, and relevant features associated with axillary lymph node metastasis were identified.

METHODS

Our retrospective study included 808 patients with cT1 invasive breast cancer treated at the Second Affiliated Hospital and the Cancer Hospital Affiliated with Harbin Medical University from February 2012 to August 2021 (250 cases in the positive axillary lymph node group and 558 cases in the negative axillary lymph node group). We allocated 564 cases to the training set and 244 cases to the verification set. R software was used to compare clinicopathological data and ultrasonic features between the two groups. Based on the results of multivariate logistic regression analysis, a nomogram prediction model was developed and verified for axillary lymph node metastasis of cT1 breast cancer.

RESULTS

Univariate and multivariate logistic regression analysis indicated that palpable lymph nodes ( P  = 0.003), tumor location ( P  = 0.010), marginal contour ( P  < 0.001), microcalcification ( P  = 0.010), surrounding tissue invasion ( P  = 0.046), ultrasonic detection of lymph nodes ( P  = 0.001), cortical thickness ( P  < 0.001) and E-cadherin ( P  < 0.001) are independently associated with axillary lymph node metastasis. Using these features, a nomogram was developed for axillary lymph node metastasis. The training set had an area under the curve of 0.869, while the validation set had an area under the curve of 0.820. Based on the calibration curve, the model predicted axillary lymph node metastases were in good agreement with reality ( P  > 0.05). Nomogram's net benefit was good based on decision curve analysis.

CONCLUSION

The nomogram developed in this study has a high negative predictive value for axillary lymph node metastasis in invasive cT1 breast c ancer. Patients with no axillary lymph node metastases can be accurately screened using this nomogram, potentially allowing this group of patients to avoid invasive surgery.

A Tale of Two Hospitals: Effect of Access to Care Through a Safety Net Hospital on Adjuvant Therapy, Imaging Compliance and 5-Year Survival Rates Compared to the University Hospital Served by the Same Breast Cancer Clinical Teams

RATIONALE AND OBJECTIVES

To compare rates of guideline-concordant care, imaging surveillance, recurrence and survival outcomes between a safety-net (SNH) and tertiary-care University Hospital (UH) served by the same breast cancer clinical teams.

MATERIALS AND METHODS

647 women with newly diagnosed breast cancer treated in affiliated SNH and UH between 11.1.2014 and 3.31.2017 were reviewed. Patient demographics, completion of guideline-concordant adjuvant chemotherapy, radiation and hormonal therapy were recorded. Two multivariable logistic regression models were performed to investigate the effect of hospital and race on cancer stage. Kaplan-Meier log-rank and Cox-regression were used to analyze five-year recurrence-free (RFS) and overall survival (OS) between hospitals and races, (p < 0.05 significant).

RESULTS

Patients in SNH were younger (mean SNH 53.2 vs UH 57.9, p < 0.001) and had higher rates of cT3/T4 disease (SNH 19% vs UH 5.5%, p < 0.001). Patients in the UH had higher rates of bilateral mastectomy (SNH 17.6% vs UH 40.1% p < 0.001) while there was no difference in the positive surgical margin rate (SNH 5.0% vs UH 7.6%, p = 0.20), completion of adjuvant radiation (SNH 96.9% vs UH 98.7%, p = 0.2) and endocrine therapy (SNH 60.8% vs UH 66.2%, p = 0.20). SNH patients were less compliant with mammography surveillance (SNH 64.1% vs UH 75.1%, p = 0.02) and adjuvant chemotherapy (SNH 79.1% vs UH 96.3%, p < 0.01). RFS was lower in the SNH (SNH 54 months vs UH 57 months, HR 1.90, 95% CI: 1.18-3.94, p = 0.01) while OS was not significantly different (SNH 90.5% vs UH 94.2%, HR 1.78, 95% CI: 0.97-3.26, p = 0.06).

CONCLUSION

In patients experiencing health care disparities, having access to guideline-concordant care through SNH resulted in non-inferior OS to those in tertiary-care UH.

Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within T2N1M0 stage hormone receptor-positive, HER2-negative breast cancer: a retrospective cohort study based on SEER database

BACKGROUND

Guideline recommendations for the application of neoadjuvant chemotherapy (NACT) in T2N1M0 stage hormone receptor-positive, HER2-negative (HR + /HER2-) breast cancer are ambiguous. The debate continues regarding whether NACT or adjuvant chemotherapy (ACT) offers superior survival outcomes for these patients.

MATERIALS AND METHODS

Female patients diagnosed with HR + /HER2- breast cancer at T2N1M0 stage between 2010 and 2020, were identified from the Surveillance, Epidemiology, and End Results database and divided into two groups, the NACT group and the ACT group. Propensity score matching (PSM) was utilized to establish balanced cohorts between groups, considering baseline features. Kaplan-Meier (K-M) analysis and the Cox proportional hazards model were executed to assess the efficacy of both NACT and ACT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). A logistic regression model was employed to examine the association between predictive variables and response to NACT.

RESULTS

After PSM, 4,682 patients were finally included. K-M curves showed that patients receiving NACT exhibited significantly worse OS and BCSS when compared with patients undergoing ACT. Multivariable Cox analysis indicated that not achieving pathologic complete response (non-pCR) after NACT (versus ACT), was identified as an adverse prognostic factor for OS (HR 1.58, 95% CI 1.36-1.83) and BCSS (HR 1.70, 95% CI 1.44-2. 02). The logistic regression model revealed that low tumor grade independently predicted non-pCR.

CONCLUSION

Among T2N1M0 stage HR + /HER2- patients, OS and BCSS of NACT were inferior to ACT. Patients who attained non-pCR after NACT demonstrated significantly worse survival outcomes compared with those who received ACT.

Survival pattern in male breast cancer: distinct from female breast cancer

Introduction

Male breast cancer (MBC) is a rare condition, and recent research has underscored notable distinctions between MBC and breast cancer in women. This study aimed to assess and contrast the long-term survival outcomes and disease patterns of MBC patients with those of their female counterparts.

Methods

We analyzed data from 113,845 patients diagnosed with breast cancer who had undergone curative surgery from the Korean Breast Cancer Registry (KBCR) between January 1990 and August 2014 in Seoul, Korea. The five-year overall survival was analyzed according to clinicopathological characteristics.

Results

Among 113,845 patients with breast cancer, 473 MBC cases were included. The median duration of follow-up was 72 months. The median age at diagnosis was 60 and 48 years for MBC and female breast cancer, respectively. Most male patients (92.6%) underwent total mastectomy, while 50.4% of female patients underwent breast-conserving surgery. Among MBC, 63.2% received chemotherapy, and 83.9% of hormone receptor-positive male patients received endocrine therapy. In survival analysis, MBC demonstrated distinct 5-year overall survival patterns compared with female breast cancer, according to age at diagnosis. In women with breast cancer, the younger age group (≤40 years) demonstrated worse 5-year overall survival than did the older age group (>40 years) (91.3% vs 92.7%, p <0.05). While in MBC, the younger age group (≤40 years) demonstrated better 5-year overall survival than did the older age group (>40 years) (97.4% vs 86.4%, p <0.05).

Discussion

In conclusion within this extensive cohort, we have revealed unique survival patterns in MBC that diverge from those observed in women with breast cancer. This study enhances our comprehension of MBC prognosis and can potentially shed light on unresolved questions, paving the way for future research in the realm of MBC.

Personalized chemotherapy selection for patients with triple-negative breast cancer using deep learning

Background

Potential uncertainties and overtreatment exist in adjuvant chemotherapy for triple-negative breast cancer (TNBC) patients.

Objectives

This study aims to explore the performance of deep learning (DL) models in personalized chemotherapy selection and quantify the impact of baseline characteristics on treatment efficacy.

Methods

Patients who received treatment recommended by models were compared to those who did not. Overall survival for treatment according to model recommendations was the primary outcome. To mitigate bias, inverse probability treatment weighting (IPTW) was employed. A mixed-effect multivariate linear regression was employed to visualize the influence of certain baseline features of patients on chemotherapy selection.

Results

A total of 10,070 female TNBC patients met the inclusion criteria. Treatment according to Self-Normalizing Balanced (SNB) individual treatment effect for survival data model recommendations was associated with a survival benefit (IPTW-adjusted hazard ratio: 0.53, 95% CI, 0.32-8.60; IPTW-adjusted risk difference: 12.90, 95% CI, 6.99-19.01; IPTW-adjusted the difference in restricted mean survival time: 5.54, 95% CI, 1.36-8.61), which surpassed other models and the National Comprehensive Cancer Network guidelines. No survival benefit for chemotherapy was seen for patients not recommended to receive this treatment. SNB predicted older patients with larger tumors and more positive lymph nodes are the optimal candidates for chemotherapy.

Conclusion

These findings suggest that the SNB model may identify patients with TNBC who could benefit from chemotherapy. This novel analytical approach may provide debiased individual survival information and treatment recommendations. Further research is required to validate these models in clinical settings with more features and outcome measurements.