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Background Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process. Methods We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion. We employed CRISPR/Cas9 to disrupt the CCCTC-Binding Factor (CTCF) binding site on an insulator element downstream of the MMP8 gene (IE8) in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. The potential of our findings to predict the progression of ductal carcinoma in situ (DCIS), was tested in data from clinical specimens. Results We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was associated with worse relapse-free (HR = 1.57 [1.06 − 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 − 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability and collagen degradation. We observed that the MMP expression pattern predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01). Conclusion Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

BackgroundMolecular testing on surgical specimens predicts disease recurrence and benefit of adjuvant chemotherapy in hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) early-stage breast cancer (EBC). Testing on core biopsies has become common practice despite limited evidence of concordance between core/surgical samples. In this study, we compared the gene expression of the 21 genes and the recurrence score (RS) between paired core/surgical specimens.MethodsEighty patients with HR+/HER2− EBC were evaluated from two publicly available gene expression datasets (GSE73235, GSE76728) with paired core/surgical specimens without neoadjuvant systemic therapy. The expression of the 21 genes was compared in paired samples. A microarray-based RS was calculated and a value ≥ 26 was defined as high-RS. The concordance rate and kappa statistic were used to evaluate the agreement between the RS of paired samples.ResultsOverall, there was no significant difference and a high correlation in the gene expression levels of the 21 genes between paired samples. However, CD68 and RPLP0 in GSE73235, AURKA, BAG1, and TFRC in GSE76728, and MYLBL2 and ACTB in both datasets exhibited weak to moderate correlation (r < 0.5). There was a high correlation of the microarray-based RS between paired samples in GSE76728 (r = 0.91, 95% confidence interval [CI] 0.81–0.96) and GSE73235 (r = 0.82, 95% CI 0.71–0.89). There were no changes in RS category in GSE76728, whereas 82% of patients remained in the same RS category in GSE73235 (κ = 0.64).ConclusionsGene expression levels of the 21-gene RS showed a high correlation between paired specimens. Potential sampling and biological variability on a set of genes need to be considered to better estimate the RS from core needle biopsy.

Identifying molecular drivers in triple-negative breast cancer (TNBC) is crucial. While HER2-low expression predicts response to novel antibody-drug conjugates, its biological influence on TNBC biology is unknown. We performed a comprehensive multi-omics analysis, integrating genomic, epigenomic, transcriptomic, and proteomic profiling to characterize HER2-low TNBC. We generated genome-wide DNA methylation profiles from a multi-institutional cohort and integrated our data with three independent cohorts (TCGA, SCAN-B, I-SPY2). TNBC cases were categorized as HER2-zero (IHC 0) or HER2-low TNBC (IHC 1+/2+, ISH non-amplified). Among 506 patients (HER2-low, n  = 288; HER2-zero, n  = 218), HER2-low TNBC exhibited significantly lower tumor mutational burden ( P  = 0.02). Epigenetic analysis identified 5287 differentially methylated sites, with consistent hypermethylation of HLA genes in HER2-low tumors. Transcriptomic analyses revealed significant downregulation of genes enriched in immune response pathways (e.g., leukocyte activation, T-cell signaling) in HER2-low TNBC (adjusted P  < 0.001). Immune cell deconvolution showed reduced immune cell infiltration in the HER2-low tumor microenvironment ( P  = 0.002). Higher expression of five immune-related genes, downregulated in HER2-low, correlated with improved relapse-free (HR = 0.52; P  < 0.001) and overall survival (HR = 0.36; P  < 0.001). HER2-low TNBC tumors display distinct molecular features compared to HER2-zero, imparting an immune-evasive phenotype. These findings provide critical insights into the unique biology of HER2-low TNBC, warranting further clinical investigation.

Background Immune checkpoint inhibitors (ICI) improve clinical outcomes in triple-negative breast cancer (TNBC) patients. However, a subset of patients does not respond to treatment. Biomarkers that show ICI predictive potential in other solid tumors, such as levels of PD-L1 and the tumor mutational burden, among others, show a modest predictive performance in patients with TNBC. Methods We built machine learning models based on pre-ICI treatment gene expression profiles to construct gene expression classifiers to identify primary TNBC ICI-responder patients. This study involved 188 ICI-naïve and 721 specimens treated with ICI plus chemotherapy, including TNBC tumors, HR+/HER2− breast tumors, and other solid non-breast tumors. Results The 37-gene TNBC ICI predictive (TNBC-ICI) classifier performs well in predicting pathological complete response (pCR) to ICI plus chemotherapy on an independent TNBC validation cohort (AUC = 0.86). The TNBC-ICI classifier shows better performance than other molecular signatures, including PD-1 ( PDCD1 ) and PD-L1 ( CD274 ) gene expression (AUC = 0.67). Integrating TNBC-ICI with molecular signatures does not improve the efficiency of the classifier (AUC = 0.75). TNBC-ICI displays a modest accuracy in predicting ICI response in two different cohorts of patients with HR + /HER2- breast cancer (AUC = 0.72 to pembrolizumab and AUC = 0.75 to durvalumab). Evaluation of six cohorts of patients with non-breast solid tumors treated with ICI plus chemotherapy shows overall poor performance (median AUC = 0.67). Conclusion TNBC-ICI predicts pCR to ICI plus chemotherapy in patients with primary TNBC. The study provides a guide to implementing the TNBC-ICI classifier in clinical studies. Further validations will consolidate a novel predictive panel to improve the treatment decision-making for patients with TNBC. Plain language summary Triple-Negative Breast Cancer (TNBC) is an aggressive type of breast cancer, responsible for a substantial burden of breast cancer-related deaths. In recent years, immunotherapy, a therapy that triggers the patient’s immune system to attack the tumor, has arisen as a promising treatment in various cancers, including TNBC. However, a subset of patients with TNBC does not respond to this treatment. Here, we employed advanced computational techniques to predict response to immunotherapy plus chemotherapy in patients with primary TNBC. Our method is more accurate than using other existing markers, such as PD-L1, but is not very accurate in patients with non-TNBC breast cancers or non-breast cancers. This method could potentially be used to better select patients for immunotherapy, upfront, avoiding the side effects and costs of treating patients in which immunotherapy might not work. Ensenyat–Mendez et al. construct a gene expression-based machine learning classifier to predict the response of triple-negative breast cancer to immune checkpoint inhibition combined with chemotherapy. Predictive performance of the 37-gene classifier is better than that of PD-1 or PD-L1.

Introduction Extreme oncoplastic breast-conserving surgery (eOBCS) describes the application of OBCS to patients who would otherwise need a mastectomy, and its safety has been previously described. Objective We aimed to compare the costs of eOBCS and mastectomy. Methods We reviewed our institutional database to identify breast cancer patients treated surgically from 2018 to 2023. We included patients with a large disease span (≥5 cm) and multifocal/multicentric disease. Patients were grouped by their surgical approach, i.e. eOBCS or mastectomy. The direct costs of care were determined and compared; however, indirect costs were not included. Results Eighty-six patients met the inclusion criteria, 10 (11.6%) of whom underwent mastectomy and 76 (88.4%) who underwent eOBCS. Six mastectomy patients (60%) had reconstruction and 6 (60%) underwent external beam radiation therapy (EBRT). Reconstructions were completed in a staged fashion, and the mean cost of the index operation (mastectomy and tissue expander) was $17,816. These patients had one to three subsequent surgeries to complete their reconstruction, at a mean cost of $45,904. The mean cost of EBRT was $5542. Thirty-four eOBCS patients (44.7%) underwent 44 margin re-excisions, including 6 (7.9%) who underwent mastectomy. Sixty (78.9%) of the eOBCS patients had EBRT. The mean cost of their index operation was $6345; the mean cost of a re-excision was $3615; the mean cost of their mastectomies with reconstruction was $49,400; and the mean cost of EBRT was $6807. The cost of care for eOBCS patients remained lower than that for mastectomy patients, i.e. $17,318 versus $57,416. Conclusion eOBCS is associated with a lower cost than mastectomy and had a low conversion rate to mastectomy.

Introduction In the era of oncoplastic breast conserving-surgery (OBCS), cosmetic outcomes and the desire for symmetry have become essential elements of the surgical management of breast cancer (BC). The timing of contralateral symmetry procedures remains a controversial topic. Simultaneous symmetry procedures (SSP) in OBCS have not been routinely offered due to the perceived risk of delayed asymmetry, potentially increasing the need for delayed cosmetic revision. This study evaluates the rate of revision after SSP in patients undergoing OBCS. Methods We reviewed our institutional prospectively maintained database identifying all BC patients treated surgically since our introduction of oncoplastic surgery in 2018. We routinely offer SSP when appropriate. Descriptive statistics evaluated oncoplastic surgical techniques, SSP offerings and procedures, perioperative complications, and revision rates after treatment completion. Results Between 2018 and 2022, 485 breast cancer patients underwent partial mastectomy, and 396 (82%) underwent OBCS. Of the 313 patients offered SSP, 272 (87%) accepted. The margin reexcision rate of this cohort was 20%. Of the 272 patients with SSP, 152 (56%) underwent intraoperative radiation therapy (IORT), and 105 (39%) had adjuvant external beam radiation therapy. Three patients (1%) experienced complications involving the symmetry side. No patients with complications experienced a delay in adjuvant therapies or requested cosmetic revisions. Three patients (1%) desired surgical revisions due to asymmetry. Conclusions Symmetry procedures at the time of OBCS are widely accepted by patients and rarely require delayed cosmetic revision. Simultaneous symmetry procedures should be routinely discussed with patients during the surgical planning of OBCS.

BackgroundRandomized, controlled trials comparing breast-conserving therapy (BCT) with mastectomy have demonstrated equivalent overall survival (OS), but recent observational studies have shown improved OS in patients undergoing BCT. These studies provide limited data on young patients who are traditionally offered mastectomy due to perceived higher disease risk. This study examines the OS in a contemporary series of young women with breast cancer undergoing upfront BCT compared with mastectomy.MethodsWomen ≤40 years old with primary invasive T1-T2, N0-N1 breast cancer were identified from the National Cancer Database between 2006 and 2016. Patient cohorts were based according to locoregional treatment: BCT, mastectomy alone (Mx), and mastectomy with radiotherapy (Mx/RT). Kaplan-Meier method followed by Cox proportional-hazards regression with inverse probability of treatment weighting (IPTW) were performed to account for treatment selection bias effects in OS.ResultsA total of 15,611 patients met the study criteria; 9,509 patients (60.9%) had BCT, 4,020 (25.8%) had Mx/RT, and 2,082 (13.3%) had Mx alone. The median follow-up was 4.6 years (interquartile range [IQR] 3.0–6.4). After IPTW-adjustment, the 5-year OS was similar for BCT (95%), Mx (95%), and Mx/RT (94%), and there was no significant difference in OS in Mx (hazard ratio [HR] = 1.16, 95% confidence interval [CI] 0.90–1.51) and Mx/RT (HR = 1.08, 95% CI 0.88–1.34) compared with BCT. Mx/RT was associated with decreased survival in patients with pT2N0 (HR = 1.78, 95% CI 1.12–2.84).ConclusionsAmong young patients with early-stage breast cancer, overall survival was equivalent regardless of surgical approach. Breast-conserving therapy remains a safe option in young women despite the clinical tendency to offer upfront mastectomy in young patients.

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet this challenge, here we profile DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers ( n  = 96). Using supervised machine learning and integration of DNA methylomes from normal, primary, and metastatic tumor specimens ( n  = 1860), we unravel epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically relevant subtypes. BrainMETH predictions are supported by routine histopathologic evaluation. We further characterize and validate the most predictive genomic regions in a large cohort of brain tumors ( n  = 165) using quantitative-methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases. The treatment of brain metastases is often limited by the ability to diagnose their origins. Here the authors generate DNA methylomes from the three most frequent types of brain metastases, identify epigenetic signatures specific to each type of metastasis and construct a DNA methylation-based classifier (BrainMETH) to advance brain metastasis diagnosis.