Heterogeneity Of Breast Cancer Research Articles

Nomograms for predicting recurrence of HER2-positive breast cancer with different HR status based on ultrasound and clinicopathological characteristics.

This study aimed to identify ultrasound and clinicopathological characteristics related to recurrence in HER2-positive (HER2+) breast cancer, and to develop nomograms for predicting recurrence. In this dual-center study, we retrospectively enrolled 570 patients with HER2+ breast cancer. The ultrasound and clinicopathological characteristics of hormone receptor (HR)-/HER2+ patients and HR+/HER2+ patients were analyzed separately according to HR status. Eighty percent of the original samples from HR-/HER2+ and HR+/HER2+ patients were extracted by bootstrap sampling as the training cohorts, while the remaining 20% were used as the external validation cohorts. Informative characteristics were screened through univariate and multivariable Cox regression in the training cohorts and used to develop nomograms for predicting recurrence. The predictive accuracy was calculated using Harrell's C-index and calibration curves. Three informative characteristics (axillary nodal status, calcification, and Adler degree) were identified in HR-/HER2+ patients, and another three (histological grade, axillary nodal status, and echogenic halo) in HR+/HER2+ patients. Based on these, two separate nomograms were constructed to assess recurrence risk. In the training cohorts, the C-index was 0.740 (95% CI: 0.667-0.811) for HR-/HER2+ nomogram, and 0.749 (95% CI: 0.679-0.820) for HR+/HER2+ nomogram. In the validation cohorts, the C-index was 0.708 (95% CI: 0.540-0.877) for HR-/HER2+ group, and 0.705 (95% CI: 0.557-0.853) for HR+/HER2+ group. The calibration curves also indicated the excellent accuracy of the nomograms. Ultrasound performance of HER2+ breast cancers with different HR status was significantly different. Nomograms integrating ultrasound and clinicopathological characteristics exhibited favorable performance and have the potential to serve as a reliable method for predicting recurrence in heterogeneous breast cancer.

Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.

Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.

Impact of Molecular Profiling on Therapy Management in Breast Cancer.

Breast cancer (BC) remains the most prevalent cancer among women and the leading cause of cancer-related mortality worldwide. The heterogeneity of BC in terms of histopathological features, genetic polymorphisms, and response to therapies necessitates a personalized approach to treatment. This review focuses on the impact of molecular profiling on therapy management in breast cancer, emphasizing recent advancements in next-generation sequencing (NGS) and liquid biopsies. These technologies enable the identification of specific molecular subtypes and the detection of blood-based biomarkers such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-educated platelets (TEPs). The integration of molecular profiling with traditional clinical and pathological data allows for more tailored and effective treatment strategies, improving patient outcomes. This review also discusses the current challenges and prospects of implementing personalized cancer therapy, highlighting the potential of molecular profiling to revolutionize BC management through more precise prognostic and therapeutic interventions.

Revealing Cellular Heterogeneity and Key Regulatory Factors of Triple-Negative Breast Cancer through Single-Cell RNA Sequencing.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). TNBC has a poor prognosis due to high intratumoral heterogeneity and metastasis, pointing to the need to explore distinct molecular subtypes and gene regulatory networks. The scRNA-seq data of five primary BC samples were downloaded from the Gene Expression Omnibus (GEO) database. Clustering was performed based on filtered and normalized data using the Seurat R package to identify marker genes, which were subsequently annotated to each subset using the CellMarker database. AUCell R package was applied to calculate the hallmark score for each epithelial cell. Marker genes of each subset were screened with FindAllMarkers and their biological functions were analyzed using the Database for Annotation Visualization and Integrated Discovery (DAVID) database. Next, cell-cell communication was performed with the CellChat R package. To identify the key regulatory genes, single-cell regulatory network inference and clustering (SCENIC) analysis was conducted. Finally, the expression and potential biological functions of the key regulatory factors were verified through cellular experiments. A total of 29,101 cells were classified into nine cell subsets, namely, Fibroblasts, Fibroepithelial cells, Epithelial cells 1, Epithelial cells 2, Epithelial cells 3, Endothelial cells, T cells, Plasma B cells and Macrophages. Particularly, the epithelial cells had a higher proportion and higher transforming growth factor-β (TGF-β) activity in the TNBC pathotype as compared to the non-TNBC pathotype. Furthermore, four epithelial cell subsets (marked as Stearoyl-CoA Desaturase (SCD1), marker of proliferation Ki67 (MKI67), Annexin A3 (ANXA3) and aquaporin 5 (AQP5)) were identified as having the greatest impact on the TNBC pathotype. Cell-cell interaction analysis revealed that ANXA3-epithelial cell subset suppressed the T cell function through different mechanisms. C-fos gene (FOS) and X-box binding protein 1 (XBP1) were considered critical regulons involved in TNBC progression. Notably, cellular experiments demonstrated that silencing XBP1 and overexpressing FOS inhibited cancer cell invasion. The four epithelial cell subsets and two critical regulons identified based on the scRNA-seq data could help explore the underlying intratumoral heterogeneity molecular mechanism and develop effective therapies for TNBC.

Integrative radiomics clustering analysis to decipher breast cancer heterogeneity and prognostic indicators through multiparametric MRI

Breast cancer diagnosis and treatment have been revolutionized by multiparametric Magnetic Resonance Imaging (mpMRI), encompassing T2-weighted imaging (T2WI), Diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced MRI (DCE-MRI). We conducted a retrospective analysis of mpMRI data from 194 breast cancer patients (September 2019 to October 2023). Using ‘pyradiomics’ for radiomics feature extraction and MOVICS for unsupervised clustering. Interestingly, we identified two distinct patient clusters associated with significant differences in molecular subtypes, particularly in Luminal A subtype distribution (p = 0.03), estrogen receptor (ER) (p = 0.01), progesterone receptor (PR) (p = 0.04), mean tumor size (p < 0.01), lymph node metastasis (LNM) (p = 0.01), and edema (p < 0.01). Our study emphasizes mpMRI’s potential in breast cancer by using radiomics-based cluster analysis to categorize tumors, uncovering heterogeneity, and aiding in personalized treatment strategies.

Comprehensive Transcriptome Analysis Expands lncRNA Functional Profiles in Breast Cancer.

Breast cancer is a heterogeneous disease that arises as a multi-stage process involving multiple cell types. Patients diagnosed with the same clinical stage and pathological classification may have different prognoses and therapeutic responses due to alterations in molecular genetics. As an essential marker for the molecular subtyping of breast cancer, long non-coding RNAs (lncRNAs) play a crucial role in gene expression regulation, cell differentiation, and the maintenance of genomic stability. Here, we developed a modular framework for lncRNA identification and applied it to a breast cancer cohort to identify novel lncRNAs not previously annotated. To investigate the potential biological function, regulatory mechanisms, and clinical relevance of the novel lncRNAs, we elucidated the genomic and chromatin features of these lncRNAs, along with the associated protein-coding genes and putative enhancers involved in the breast cancer regulatory networks. Furthermore, we uncovered that the expression patterns of novel and annotated lncRNAs identified in breast cancer were related to the hormone response in the PAM50 subtyping criterion, as well as the immune response and progression states of breast cancer across different immune cells and immune checkpoint genes. Collectively, the comprehensive identification and functional analysis of lncRNAs revealed that these lncRNAs play an essential role in breast cancer by altering gene expression and participating in the regulatory networks, contributing to a better insight into breast cancer heterogeneity and potential avenues for therapeutic intervention.

Opportunities and Challenges in the Development of Antibody-Drug Conjugate for Triple-Negative Breast Cancer: The Diverse Choices and Changing Needs.

Triple-negative breast cancer (TNBC) is a highly heterogeneous breast cancer subtype, which is also characterized by the aggressive phenotype, high recurrence rate, and poor prognosis. Antibody-drug conjugate (ADC) is a monoclonal antibody with a cytotoxic payload connected by a linker. ADC is gaining more and more attention as a targeted anti-cancer agent. Clinical studies of emerging ADC drugs such as sacituzumab govitecan and trastuzumab deruxtecan in patients with metastatic breast cancer (including TNBC) are progressing rapidly. In view of its excellent clinical efficacy and good tolerability, Sacituzumab govitecan gained accelerated approval by the FDA for the treatment of advanced metastatic TNBC in 2020. This review discusses the treatment status and challenges in TNBC, with an emphasis on the current status of ADC development and clinical trials in TNBC and metastatic breast cancer. We also summarize the clinical experience and future exploration directions of ADC development for TNBC patients.

YWHAB is regulated by IRX5 and inhibits the migration and invasion of breast cancer cells.

Highly metastatic and heterogeneous breast cancer affects the health of women worldwide. Abnormal expression of tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein β (YWHAB), also known as 14-3-3β, is associated with the tumorigenesis and progression of bladder cancer, lung cancer and hepatocellular carcinoma; however, to the best of our knowledge, the role of YWHAB in breast cancer remains unknown. In the present study, a dual luciferase assay demonstrated that the transcription factor iroquois homeobox 5 may regulate YWHAB expression by affecting the promoter sequence upstream of its transcription start site. Subsequently, it was demonstrated that overexpression of YWHAB did not affect proliferation, but did reduce the migration and invasion of MDA-MB-231 cells. Furthermore, knockdown of YWHAB promoted the migration and invasion of MCF7 cells. Transcriptomics analysis demonstrated that when YWHAB was overexpressed, 61 genes were differentially expressed, of which 43 genes were upregulated and 18 genes were downregulated. These differentially expressed genes (DEGs) were enriched in cancer-related pathways, such as 'TNF signaling pathway' [Kyoto Encyclopedia of Genes and Genomes (KEGG): map04688]. The pathway with the largest number of DEGs was 'Rheumatoid arthritis' (KEGG: map05323). Notably, YWHAB downregulated vimentin, which is a mesenchymal marker, thus suggesting that it may weaken the mesenchymal properties of cells. These findings indicate that YWHAB may be a potential therapeutic target in breast cancer and further work should be performed to assess its actions as a potential tumor suppressor.

Single-cell profiling of surface glycosphingolipids opens a new dimension for deconvolution of breast cancer intratumoral heterogeneity and phenotypic plasticity

Glycosylated sphingolipids (GSLs) are a diverse group of cellular lipids typically reported as being rare in normal mammary tissue. In breast cancer (BCa), GSLs have emerged as noteworthy markers associated with breast cancer stem cells, mediators of phenotypic plasticity, and contributors to cancer cell chemoresistance. GSLs are potential surface markers that can uniquely characterize the heterogeneity of the tumor microenvironment, including cancer cell subpopulations and epithelial–mesenchymal plasticity (EMP). In this study, mass spectrometry analyses of the total sphingolipidome in breast epithelial cells and their mesenchymal counterparts revealed increased levels of Gb3 in epithelial cells and significantly elevated GD2 levels in the mesenchymal phenotype. To elucidate if GSL-related epitopes on BCa cell surfaces reflect EMP and cancer status, we developed and rigorously validated a 12-color spectral flow cytometry panel. This panel enables the simultaneous detection of native GSL epitopes (Gb3, SSEA1, SSEA3, SSEA4, and GD2), epithelial–mesenchymal transition markers (EpCAM, TROP2, and CD9), and lineage markers (CD45, CD31, and CD90) at the single-cell level. Next, the established panel was used for the analysis of BCa primary tumors and revealed surface heterogeneity in SSEA1, SSEA3, SSEA4, GD2, and Gb3, indicative of native epitope presence also on non-tumor cells. These findings further highlighted the phenotype-dependent alterations in GSL surface profiles, with differences between epithelial and stromal cells in the tumor. This study provides novel insights into BCa heterogeneity, shedding light on the potential of native GSL-related epitopes as markers for EMP and cancer status in fresh clinical samples. The developed single-cell approach offers promising avenues for further exploration.

Pathologic complete response to KEYNOTE522 and HER2-directed therapy for synchronous TNBC and HER2+ breast cancer

Simultaneous presentation of two separate primary breast cancers of differing histology at initial diagnosis is an uncommon phenomenon; it is even rarer to find these pathologically distinct populations within the same biopsy. Here we report the case of a patient diagnosed with clearly demarcated, pathologically heterogenous triple negative breast cancer (TNBC) and HER2+ breast cancer that was treated with a hybrid chemoimmunotherapy regimen combining elements of Keynote-522 and a standard HER2-directed neoadjuvant regimen, yielding apathologic complete response by the time of surgery with no notable adverse events. Molecular analysis of the histologically distinct tumor populations confirmed molecular evidence of differential HER2 expression but also suggested clonal relatedness of the two tumor populations based upon mutational profile, with phenotypic divergence potentially resulting from copy number alterations in NF1. Overall, this case highlights a rare histologic phenomenon that was successfully treated by combining both TNBC and HER2 directed neoadjuvant therapies.

Unveiling heterogeneity and prognostic markers in ductal breast cancer through single-cell RNA-seq

BackgroundBreast cancer (BC) is a heterogeneous disease, with the ductal subtype exhibiting significant cellular diversity that influences prognosis and response to treatment. Single-cell RNA sequencing data from the GEO database were utilized in this study to investigate the underlying mechanisms of cellular heterogeneity and to identify potential prognostic markers and therapeutic targets.MethodsBioinformatics analysis was conducted using R packages to analyze the single-cell sequencing data. The presence of highly variable genes and differences in malignant potency within the same BC samples were examined. Differential gene expression and biological function between Type 1 and Type 2 ductal epithelial cells were identified. Lasso regression and Cox proportional hazards regression analyses were employed to identify genes associated with patient prognosis. Experimental validation was performed in vitro and in vivo to confirm the functional relevance of the identified genes.ResultsThe analysis revealed notable heterogeneity among BC cells, with the presence of highly variable genes and differences in malignant behavior within the same samples. Significant disparities in gene expression and biological function were identified between Type 1 and Type 2 ductal epithelial cells. Through regression analyses, CYP24A1 and TFPI2 were identified as pivotal genes associated with patient prognosis. Kaplan-Meier curves demonstrated their prognostic significance, and experimental validation confirmed their inhibitory effects on malignant behaviors of ductal BC cells.ConclusionThis study highlights the cellular heterogeneity in ductal subtype breast cancer and delineates the differential gene expressions and biological functions between Type 1 and Type 2 ductal epithelial cells. The genes CYP24A1 and TFPI2 emerged as promising prognostic markers and therapeutic targets, exhibiting inhibitory effects on BC cell malignancy in vitro and in vivo. These findings offer the potential for improved BC management and the development of targeted treatment strategies.

Heterogeneous Evolution of Breast Cancer Cells-An Endogenous Molecular-Cellular Network Study.

Breast cancer heterogeneity presents a significant challenge in clinical therapy, such as over-treatment and drug resistance. These challenges are largely due to its obscure normal epithelial origins, evolutionary stability, and transitions on the cancer subtypes. This study aims to elucidate the cellular emergence and maintenance of heterogeneous breast cancer via quantitative bio-process modeling, with potential benefit to therapeutic strategies for the disease. An endogenous molecular-cellular hypothesis posits that both pathological and physiological states are phenotypes evolved from and shaped by interactions among a number of conserved modules and cellular factors within a biological network. We hereby developed a model of core endogenous network for breast cancer in accordance with the theory, quantifying its intrinsic dynamic properties with dynamic modeling. The model spontaneously generates cell states that align with molecular classifications at both the molecular and modular level, replicating four widely recognized molecular subtypes of the cancer and validating against data extracted from the TCGA database. Further analysis shows that topologically, a singular progression gateway from normal breast cells to cancerous states is identified as the Luminal A-type breast cancer. Activated positive feedback loops are found to stabilize cellular states, while negative feedback loops facilitate state transitions. Overall, more routes are revealed on the cellular transition between stable states, and a traceable count explains the origin of breast cancer heterogeneity. Ultimately, the research intended to strength the search for therapeutic targets.

Salivary Biomarkers in Breast Cancer: From Salivaomics to Salivaoncoomics.

Saliva is a promising biological fluid for the diagnosis and monitoring of diseases, including breast cancer. To study the composition of saliva, a complex of "omics" technologies is used: genomics, transcriptomics, proteomics, metabolomics and microbiomics. In this review, we systematized all known "omics" in their application to saliva analysis in breast cancer in order to understand how complete the picture is provided by the combination of different areas of research and to identify missing links. It has been shown that studies of saliva in breast cancer are chaotic and unsystematic. Inconsistency of sample sizes and high heterogeneity of breast cancer were identified. The main tasks that need to be solved for the complete and harmonious development of salivaomics in a new direction-"salivaonkoomics" are formulated. Thus, it is necessary to systematize and unify the study of biomarkers within each area of "omics", including sample size and its homogeneity, a list of methods and approaches, a list of biomarkers, reproducibility of results, and the ability to transfer results to other samples. It is important to expand the number of components of "omics" by adding new methods (for example, spectralomics, etc.), as well as studying the relationships between different "omics" technologies (interactomics). All this together will allow the study of saliva not only in breast cancer but also in many other pathologies to a qualitatively new level.

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

RB1 Genetic Alterations in Estrogen Receptor–Positive Breast Carcinomas: Correlation With Neuroendocrine Differentiation

Genetic alterations in the retinoblastoma susceptibility gene (RB1) are present in up to 40% of triple-negative breast cancers (BCs) and frequent in tumors with neuroendocrine differentiation, including small cell neuroendocrine carcinoma. Data on RB1 genetic alterations in estrogen receptor (ER)–positive BCs are scarce. In this study, we sought to define the morphologic, immunohistochemical, and genetic features of ER-positive BCs harboring somatic alterations in RB1, with emphasis on neuroendocrine differentiation. ER-positive BCs with pathogenic RB1 genetic alterations were identified in <1% of cases (N = 55) from a cohort of 6026 BCs previously subjected to targeted next-generation sequencing, including 23 primary BCs (pBCs) and 32 recurrent/metastatic BCs (mBCs). In cases where loss of heterozygosity of the wild-type RB1 allele could be assessed (93%, 51/55), most pBCs (82%, 18/22) and mBCs (90%, 26/29) exhibited biallelic RB1 inactivation, primarily through loss-of-function mutation and loss of heterozygosity (98%, 43/44). Upon histologic review, a subset of RB1-altered tumors exhibited neuroendocrine morphology (13%, 7/55), which correlated with expression of neuroendocrine markers (39%, 9/23) in both pBCs (27%, 3/11) and mBCs (50%, 6/12). Loss of Rb protein expression was observed in BCs with biallelic RB1 loss only, with similar frequency in pBCs (82%, 9/11) and mBCs (75%, 9/12). All cases with neuroendocrine marker expression (n = 9) and/or neuroendocrine morphology (n = 7) harbored biallelic genetic inactivation of RB1 and exhibited Rb loss of expression. TP53 (53%, 29/55) and PIK3CA (45%, 25/55) were the most frequently comutated genes across the cohort. Overall, these findings suggest that ER-positive BCs with biallelic RB1 genetic alterations frequently exhibit Rb protein loss, which correlates with neuroendocrine differentiation in select BCs. This study provides insights into the molecular and phenotypic heterogeneity of BCs with RB1 genetic inactivation, underscoring the need for further research into the potential clinical implications associated with these tumors.

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer.

Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

Molecular profiling in ABC: Is complementary testing with tissue and plasma necessary and clinically relevant?

e12566 Background: This retrospective analysis explores the concordance between molecular analyses of tissue and plasma amongst Advanced Breast Cancer (ABC) patients and investigates the utility of simultaneous profiling for enhanced clinical insights. Methods: A total of 187 (177 Cancertrack paired and 10 Guardant 360) patient samples with availability of both tissue and ctDNA specimens, were subjected to comparative molecular profiling. Median age was 52 years (Range 23 – 82 years), 174 (93%) patients had advanced breast cancer and 177 (95%) patients had received prior treatments. We assigned tier 1 status to predictive biomarkers with FDA approved or guideline recommended therapies in breast cancer. Tier 2 status was assigned to alterations for which therapies were approved in different tumor type. Tier 3 had either clinical evidence in small studies or had clinical trial inclusion criteria. Results: Paired tissue-ctDNA profiling showed 139/187 (74%) samples had at least one concordant molecular alteration. Simultaneous tissue and ctDNA profiling led to the opportunity to offer Tier 1 recommended therapies in 113/187 (60%) patients. Amongst these, 71/113 (63%) exhibited concordance in tissue and circulating free DNA (cfDNA). ctDNA missed Tier 1 alterations in 14 patients which were detected by tissue biopsy. On the contrary tissue biopsy failed to detect Tier 1 alterations in 18 patients which were identified by ctDNA only. When Tier 2 and 3 alterations were considered, ctDNA identified additional alterations compared to tissue in 29 patients (37 variants), whereas tissue identified additional alterations in 20 patients (24 variants). Complementary tissue and ctDNA profiling showed alterations with potential to impact clinical management (Tier1/2/3) in 82% patients. When including only Tier 1 and 2 alterations, simultaneous profiling approach gives an opportunity to offer personalized therapy in 68% patients. The Tier1 ctDNA only alterations were most frequent in ESR1 gene. In fact, a total of a total of 29 ESR1 mutations were detected in these patients, of which 10 mutations were detected in both tissue and liquid. In 3 patients’ tissues were positive for ESR1 mutations but the corresponding ctDNA was negative. Similarly, ctDNA detected 16 ESR1 variants which were negative in the tissue sample. The most common ESR1 variants were D538G and Y537S. Conclusions: The simultaneous profiling of tissue and ctDNA enhanced overall clinical utility of molecular analysis in advanced breast cancer by identifying predictive biomarkers. The integration of data from both sources allowed for comprehensive understanding of the molecular heterogeneity in breast cancer. It underscores the potential of simultaneous profiling to guide treatment decisions and improve patient outcomes. By detecting acquired resistance ESR1 mutations more effectively, ctDNA serves as a valuable tool for monitoring as well.

Biomarker discordance after neoadjuvant systemic therapy and associated patterns of recurrence.

3149 Background: Understanding and addressing intratumor heterogeneity in breast cancer (BC) is crucial for advancing research and improving patient outcomes. The identification of biomarkers for targeted therapies is complex when dealing with heterogeneous tumors, and this heterogeneity complicates cancer outcomes since it affects treatment response, and the development of resistance. Methods: A single institution retrospective review of patients with BC who received neoadjuvant systemic therapy (NAST) followed by definitive surgical resection from 2008 to 2022 was performed. Initial tumor biopsies were tested for hormone receptors (HR) [estrogen receptor (ER) and progesterone receptor (PR)], and HER2 status and repeated on the residual tumor tissue after NAST. HER2 status was categorized into HER2-negative, HER2-low, and HER2-positive and HR status was categorized into ER and/or PR positive or negative based on the 2023 ASCO-CAP guidelines. HER2 and HR concordance and discordance rates were obtained and patients who had disease recurrence were identified and analyzed using descriptive statistics and Fisher’s exact test. Results: 480 patients with BC received NAST, and 143 patients with residual disease had pre and post treatment biomarker data available for analysis with a median post-surgery follow up of 15.2 months. Discordance in either HER2 or HR status was identified in 50% (72/143) of samples. Out of 143 patients, 44 patients had disease recurrence in which 50% (22/44) of tumors exhibited biomarker discordance. Among the changes in biomarker status, a shift in PR expression occurred most frequently in 27% of tumors (12/44). A change from HER2-low to HER2-negative status, as well as changes in ER expression occurred in 11% of tumors (5/44). 14% (6/44) of tumors had changes in both HER2 and HR. In patients who did not have recurrence, 51% (50/99) of tumors exhibited biomarker discordance. A HER2-low to HER2-negative status occurred most frequently in 18% (18/99). A change in ER expression occurred second most frequently, in 14% (14/99) of tumors. There was no statistical significance of discordance rates in the recurrence group and non-recurrence group (p-value=0.96). Conclusions: Tumor heterogeneity plays a role in shaping the distinct tumor biology of each patient. While the rates of biomarker discordance were comparable between samples with and without recurrence, the importance of HR discordance in this group requires extensive long-term monitoring. Our research highlights the importance of biomarker changes in a curative setting. Considering the implications for treatment, further investigation into additional biological and tumor-related factors associated with recurrence is warranted. [Table: see text]

Identifying mutations in ctDNA to predict antibody-drug conjugate response in breast cancer.

e13074 Background: Metastatic breast cancer (mBC) is a complex disease, and outcomes remain poor because new therapies are needed. A new class of drugs, antibody-drug conjugate (ADC), has shown effectiveness across all breast cancer subtypes. Yet FDA- approval for these therapies is restricted only to HER2 and triple-negative subtypes. Therefore, we urgently need to identify which patients, regardless of subtype, will respond to ADCs. The advent of circulating tumor DNA (ctDNA) offers a unique noninvasive method to capture breast cancer (BC) heterogeneity. Recently, ctDNA testing has been employed in clinical practice to guide targeted therapies for mBC, particularly in cases of hormone receptor positive (HR+) disease with mutations in PIK3CA and ESR1. The clinical implications to predict response to ADC therapy in BC remains unclear. Here we test the hypothesis that ctDNA can detect mutations that predict response to novel ADCs. Methods: We analyzed a subset of patients from the Dallas Metastatic Breast Cancer Study comprised of patients with mBC who underwent ctDNA testing using the Tempus xF liquid biopsy ctDNA sequencing panel. The data was analyzed from a single academic medical center between the initial year of ctDNA collection in 2019 to 2023. We identified detectable mutations from patients and addressed a relationship by using Metascape. Relevant signaling pathways were identified: APOBEC, ErbB signaling, p53 and Ras-MAPK pathway. Patients with triple negative, HER2, and HR BC were examined for ADC response and associated mutations. Survival analyses were estimated using Kaplan-Meier and Gehan Breslow Wilcoxon test for statistical analysis. Results: We identified 43 patients with HR+ mBC who had at least one mutation within the Ras-MAPK pathway and 10 of 43 received ADC therapy. Median survival of patients who received ADC therapy 58 months (n=10) vs not receiving ADC therapy 33 months (n=33) (p &lt; 0.05). Of the ten patients who received ADC treatment, 60% had 1+ HER2 staining on tissue biopsy. 70% of patients received Trastuzumab deruxtecan (T-DXd) and 30% received Sacituzumab govitecan (SG). SG was given to patients with negative HER2 staining on biopsy. Patients with at least one mutation within ABOBEC, ErbB signaling, and p53 pathways did not have statistically significant differences in mOS. Conclusions: In HR+ mBC, detection of mutated genes associated with the Ras-MAPK pathway by ctDNA was associated with a more favorable response when treated with ADCs. These findings are exciting because HR+ BCs are being targeted with ADCs regardless of HER2 or TROP2 expression, highlighting the need for new biomarkers to distinguish which HR+ patients to treat. Our retrospective analysis findings are limited by the number of patients with ctDNA testing and also timing of testing. Further studies are needed to solidify the observed correlation between Ras-MAPK pathway mutations and favorable response to ADC treatment.

Factors associated with benefit of adjuvant chemotherapy in patients with T1b/T1c HR-positive/HER2-negative breast cancer and high multigene recurrence score.

e12540 Background: Patients diagnosed with early-stage HR-positive/HER2-negative Breast Cancer (BC) and high Oncotype DX Recurrence Score (RS ≥26) are offered adjuvant chemotherapy and endocrine therapy compared (CET) to endocrine therapy alone (ET). We sought to investigate if additional clinical factors that could further determine benefit from chemotherapy in patients with T1b/T1c and N0 tumors with high Oncotype DX to help deescalate treatment by avoiding chemotherapy induced toxicity. Methods: The purpose of this study is to determine the clinical factors associated with a survival difference from CET compared to ET alone in T1b/T1c and N0 BC. We analyzed the record of patients diagnosed with T1b/T1cN0M0 HR-positive/HER2-negativeBC and RS ≥26 between 2006 and 2020 from the National Cancer Database. Patients were separated into two groups based on their treatment: CET or ET and the following characteristics were assessed: age, grade, histology, and RS (26-30, 31-40, 41-100) to determine overall survival differences among the two groups. Chi-square was performed to evaluate the association between baseline categorical characteristic variable and chemotherapy treatment. Survival analysis of treatment modalities using Kaplan Meier curves and univariate Cox regression. Multivariate Cox regression with backwards elimination was performed for subgroup analyses. Results: A total of N=19,373 eligible patients were identified, n=14,422 (74.4%) received CET and the rest ET alone. The mean age at diagnosis was 59.6 years (SD=10.3); 86.6% presented with invasive ductal carcinoma and 83.3% had a Charlson-Deyo Comorbidity Score of 0. In the overall group, patients who received CET had a higher median overall survival than endocrine therapy alone (65.7 versus 52.1 months, log-rank p-value&lt;.0001). However, further analysis noted that treatment with CET showed better outcome compared to ET alone in the following subgroups of patients: invasive ductal histology (95% OS 65.5 versus 52.7 months, log-rank p-value&lt;.0001) and RS &gt;30 (95% OS 63.6 versus 40.5 months, log-rank p-value&lt;.0001). Importantly, multivariable cox regression subgroup analysis revealed no significant overall survival difference among the subgroup of patients with T1b/T1c and low grade (p=0.286) or RS 26-30 (p=0.200) with CET compared to ET alone. Conclusions: This large database confirms the heterogeneity of BC in patients with low burden disease despite high Oncotype.While patients diagnosed with T1b/T1cN0M0 and high RS (&gt;30) could benefit from CET compared to ET alone as per standard practice, additional criteria could be considered in this group including low grade or RS 26-30 to better determine which population of patients do not benefit from the addition of chemotherapy and accordingly individualized chemotherapy decision might be made to minimize toxicity.