Heterogeneity Of Breast Cancer Research Articles

Halofuginone-guided nano-local therapy: Nano-thermosensitive hydrogels for postoperative metastatic canine mammary carcinoma with scar removal

In female dogs, the highest morbidity and mortality rates cancer are the result of mammary adenocarcinoma, which presents with metastases in the lung. Other than early surgical removal, however, no special methods are available to treat mammary adenocarcinoma. Because human breast cancer and canine mammary carcinoma share clinical characteristics and heterogeneity, the canine model is a suitable spontaneous tumor model for breast cancer in humans. In this study, the physical swelling method was used to prepare halofuginone-loaded D-α-tocopherol polyethylene glycol 1000 succinate (TPGS) polymer micelles nano-thermosensitive hydrogels (HTPM-gel). Furthermore, HTPM-gel was investigated via characterization, morphology, properties such as swelling experiment and in vitro release with reflecting its splendid nature. Moreover, HTPM-gel was further examined its capability to anti-proliferation, anti-migration, and anti-invasion. Ultimately, HTPM-gel was investigated for its in vivo anticancer activity in the post-operative metastatic and angiogenic canine mammary carcinoma. HTPM-gel presented spherical under transmission electron microscope (TEM) and represented grid structure under scanning electron microscope (SEM), with hydrodynamic diameter (HD) of 20.25 ± 2.5 nm and zeta potential (ZP) of 15.10 ± 1.82 mV. Additionally, HTPM-gel own excellent properties comprised of pH-dependent swelling behavior, sustained release behavior. To impede the migration, invasion, and proliferation of CMT-U27 cells, we tested the efficacy of HTPM-gel. Evaluation of in vivo anti-tumor efficacy demonstrates HTPM-gel exhibit a splendid anti-metastasis and anti-angiogenic ability, with exhibiting ideal biocompatibility. Notably, HTPM-gel also inhibited the scar formation in the healing process after surgery. In summary, HTPM-gel exhibited anti-metastasis and anti-angiogenic and scar repair features. According to the results of this study, HTPM-gel has encouraging clinical potential to treat tumors with multifunctional hydrogel.

Determination of target genes for classified molecular subtypes of triple-negative breast cancer form microarray gene expression profiling: An integrative in silico approach.

Highly heterogeneous triple-negative breast cancer (TNBC) has tough clinical features, which were gradually solving and improving in diagnosis by the molecular subtyping of TNBC. Presently, this study was focused on analyzing the genetic makeup of TNBC subtypes. This study explored the MicroArray expression profiling of differentially expressed genes in molecular subtypes BL1, BL2, IM, luminal androgen receptor, M, and mesenchymal stem-like of TNBC by analyzing the Gene Expression Omnibus dataset GSE167213. Various gene ontologies-based protein-protein interaction (PPI) networks were subtyped TNBC genes. The effect of genetic alteration on TNBC cases was also interpreted. The MicroArray gene expression profiling was done through R programming and subjected to functional annotation through the database for annotation, visualization, and integrated discovery. The PPI networking of functionally associated genes was interpreted by STRING. The survival analysis was done through cBioPortal. The t -test was used through R programming to generate the P values for a test of the significance of expressed genes. A total of 54,613 significant probes were analyzed in the TNBC MicroArray dataset. The functional PPI networks of BL1, BL2, and IM upregulated genes showed significant associations. The survival analysis of differentially expressed genes showed the significant prognostic effect of 32 upregulated genes of different subtypes on TNBC cases with genetic alterations, whereas the remaining genes showed no significant effects. The output of the present study provided significant target gene panels for different TNBC subtypes, which would add an informative genetic value to TNBC diagnosis.

Abstract 6628: Mapping the spatial and molecular determinants of macrophage heterogeneity in breast cancer

Abstract Tumor-infiltrating macrophages support critical steps in tumor progression, and their accumulation in the tumor microenvironment (TME) is associated with adverse outcomes and therapeutic resistance across human cancers. In the TME, macrophages adopt diverse phenotypic alterations, giving rise to heterogeneous immune activation states and induction of cell cycle. While the transcriptional profiles of these activation states are well-annotated across human cancers, the underlying signals that regulate macrophage heterogeneity and accumulation remain incompletely understood. Here, we leveraged a novel ex vivo organotypic TME (oTME) model of breast cancer, in vivo murine models, and human samples to map the determinants of functional heterogeneity of TME macrophages. We identified a subset of F4/80high Sca-1+ self-renewing macrophages maintained by type-I interferon (IFN) signaling and requiring physical contact with cancer-associated fibroblasts. We discovered that the contact-dependent self-renewal of TME macrophages is mediated via Notch4, and its inhibition abrogated tumor growth of breast and ovarian carcinomas in vivo, as well as lung dissemination in a PDX model of triple-negative breast cancer (TNBC). Through spatial multi-omic profiling of protein markers and transcriptomes, we found that the localization of macrophages further dictates functionally distinct but reversible phenotypes, regardless of their ontogeny. Whereas immune-stimulatory macrophages (CD11C+CD86+) populated the tumor epithelial nests, the stroma-associated macrophages (SAMs) were proliferative, immunosuppressive (Sca-1+CD206+PD-L1+), resistant to CSF-1R depletion, and associated with worse patient outcomes. Notably, following cessation of CSF-1R depletion, macrophages rebounded primarily to the SAM phenotype, which was associated with accelerated growth of mammary tumors. Our work reveals the spatial determinants of macrophage heterogeneity in breast cancer and highlights the disruption of macrophage self-renewal as a potential new therapeutic strategy. Citation Format: Nir Ben Chetrit, Xiang Niu, Jesus Sotelo, Ariel Swett, Vinagolu Rajasekhar, Maria Jiao, Caitlin Stewart, Priya Bhardwaj, Sanjay Kottapalli, Saravanan Ganesan, Pierre-Louis Loyher, Catherine Potenski, Kristy Brown, Neil M. Iyengar, Dilip D. Giri, Scott W. Lowe, John H. Healey, Frederic Geissmann, Irit Sagi, Johanna A. Joyce, Dan A. Landau. Mapping the spatial and molecular determinants of macrophage heterogeneity in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6628.

Abstract 5483: Macrospatial ecotype heterogeneity in early-stage breast cancer identified by spatial nucleus barcoding

Abstract Ductal carcinoma in situ (DCIS), the predominant form of early-stage breast cancer and a precursor to invasive breast cancer, remains inadequately understood in terms of spatial microenvironment reprogramming. In this study, we developed a Spatial Nucleus Barcoding (SNuBar) approach for single-nucleus RNA sequencing (SNuBar-RNA) that utilizes a single oligonucleotide adaptor to preserve spatial information. The accuracy and scalability of SNuBar was validated using cell line mixture experiments. We then applied SNuBar-RNA to investigate the macrospatial ecotype heterogeneity in early-stage breast cancer. By analyzing single cells from different macrodissected spatial regions in normal breast tissues, matched normal and DCIS tissues, we identified 13 major cell types and 43 distinct cell states, co-localizing in diverse combinations across four primary topographic areas (adipose-enriched, normal epithelial, activated stroma and tumor). Spatial analysis revealed the reprogramming of vascular and myoepithelial cells in localized zones near premalignant cells, while fibroblasts, T-cells, and myeloid cells exhibited reprogramming across broader fields. Validation using the MERSCOPE assay confirmed stromal heterogeneity between tumor and normal areas. Collectively, our data shows that many diverse cell types are reprogrammed in spatially-defined areas in the early-stage breast cancer microenvironment, relative to the normal breast tissue regions. Citation Format: Kaile Wang, Zhenna Xiao, Yiyun Lin, Runmin Wei, Shanshan Bai, Jie Ye, Rui Ye, Min Hu, Aatish Thennavan, Emi Sei, Alastair Thompson, Savitri Krishnamurthy, Nicholas Navin. Macrospatial ecotype heterogeneity in early-stage breast cancer identified by spatial nucleus barcoding [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5483.

Abstract 7353: Exploring intrapatient heterogeneity in metastatic breast cancer: Insights into tumor evolution from a warm procurement trial

Abstract Metastatic breast cancers show variable clinical responses due to inherent heterogeneity, both within tumors and among patients. Studies mainly examine molecular diversity across different patients' tumors and genetic variance within a single tumor. Yet, the variability among multiple tumors or metastases in a single patient remains underexplored. Our study investigates this intrapatient heterogeneity, examining cell and tumor evolution from a single genetic source in metastatic breast cancer. In a warm procurement trial involving 6 patients with multi-site tumors, samples were collected for detailed molecular analysis. Whole exome sequencing (WES) and single-cell RNA sequencing (scRNA-seq) were used to analyze genetic similarities and disparities. WES data revealed mutational patterns and copy number alterations, showing homogeneity and heterogeneity in tumors within patients. Further, phylogenetic analysis with scRNA-seq variant calls paired with transcriptional phenotypes uncovered a MYC-enriched subclonal population in a metastatic site. Integrating WES and scRNA-seq data provided a clearer understanding of the genomic and phenotypic features in and between patients. Our WES study revealed significant interpatient variations in genetic drivers and CNA profiles. Among five patients, two showed APOBEC and HR mutations, linked to increased tumor mutations. Despite general genetic homogeneity, there were exceptions. Tumors in Patient 3's upper lymph nodes had distinct genetics compared to abdominal tumors. Unique genetic patterns were also noted in the pancreas and mesentery of Patients 3 and 7, respectively. Genetic findings were supported by transcriptional analysis, showing distinct expression patterns in specific sites. Phylogenetic analysis highlighted intratumor heterogeneity, as shown by variations in phylogenetic composition and gene expression across samples. Notably, in patients with the most samples (Patients 3 and 7), a conserved cell clade, evolved early and primarily located in a single site, displayed a high proliferation gene expression signature closely associated with Myc activity. This underscores the importance of early clonal expansions in tumor evolution and suggests potential therapeutic targets in these early, proliferative cells. Our study highlights the vital role of intrapatient heterogeneity in understanding cancer complexity and treatment resistance. By analyzing genetic and phenotypic variability in multi-site tumors within patients, and Myc's key role in tumor growth and evolution, our research offers new insights into tumor evolution. This underscores the need for personalized oncology treatments based on each patient's tumor genetics. Citation Format: Isaac Bishara, Xuan Liu, Jason Griffiths, Jiayi Liu, Patrick Cosgrove, Jasmine R. McQuerry, Feng Chi, Pierre Wallet, Vince K. Grolmusz, Benjamin Copeland, Lance Pflieger, Jinfeng Chen, Sumana Majumdar, Grace Ronquillo, Terron Crowder, Rena Emond, Rachel Factor, Eliza Barragan, David Bowtell, Adam Cohen, Daniel D. Schmolze, Peter Lee, Kena Ihle, Lusine Tumyan, Aritro Nath, James Waisman, Andrea Bild, Jeff Chang. Exploring intrapatient heterogeneity in metastatic breast cancer: Insights into tumor evolution from a warm procurement trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7353.

Abstract 6604: Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer

Abstract BACKGROUND: Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer and only ~40% of TNBC patients achieve a pathological complete response (pCR) following neoadjuvant chemotherapy (NACT). Since molecular heterogeneity of TNBC may contribute to variable responses to NACT, we aimed to deconvolute TNBC’s histological and spatial transcriptomics (ST) patterns. METHODS: In total, 90 pre-treatment biopsies were collected from NACT-treated TNBC patients from archival samples and the ongoing FORCE (NCT03238144) clinical trial at Guy’s Hospital, London, UK. Of these, 38 achieved pCR (Responder), 46 had residual disease (Non-Responder) whilst 6 are currently undergoing NACT; 46 post-treatment surgical resections were collected from Non-Responders.Each sample was H&E stained, imaged, and annotated by a pathologist. A 6-digit classifier was designed to capture the histology of each region of interest (ROI), characterizing the tumour region, epithelial type and immune cell localization, population, distribution, and abundance.H&Es were used to guide ST profiling of serial sections which was performed on the GeoMx Digital Spatial Profiler. Tissues were stained with fluorescent antibodies against PanCK and CD45 to visualize the tissue, select ROIs and illuminate spatially resolved tumor and immune-enriched compartments, defined as PanCK+/CD45- and PanCK-/CD45+, respectively.Data analysis was performed in R 4.3.1 using the limma, dplyr, EdgeR, GeoMx Tools, GeoMx Workflows, RUV4, Spatial Experiment, SpatialDecon and GSVA packages, facilitating quality control, batch correction, differential and topographical gene expression, immune cell deconvolution and gene set enrichment analysis (GSEA), respectively. RESULTS: To date, we have performed ST profiling of 120 TNBC samples from 82 patients (46 Non-Responders; 36 Responders), totaling 3917 tumor or immune-cell enriched regions. Preliminary analyses revealed KEGG pathways involved in tissue adhesion are upregulated in tumor compartments of Non-Responders compared to Responders, whilst those involved in genomic integrity are suppressed. Unsupervised clustering of PanCK+CD45- regions in Non-Responders identified tumor clusters present in both pre- and post-NACT samples, suggesting potential chemo-resistant properties. Moreover, immune cell deconvolution of the PanCK-/CD45+ regions revealed spatially distinct patters of immune cell composition mapped to histological annotations identified by our ROI classifier. CONCLUSION: (S)Large scale ST of TNBC before and after NACT reveals novel patterns associated with response to treatment. We have designed a novel ROI classifier to spatially resolved transcriptomes of histological features, as such provide an in-depth characterization of the histo-genomics of TNBC. Citation Format: Isobelle Wall, Jelmar Quist, Sarah Pinder, KCL Cancer Biobank, Sheeba Irshad, Cheryl Gillet, Victoria Seewaldt, Kavitha Mukund, David Frankhouser, Shankar Subramaniam, Maddy Parsons, Anita Grigoriadis. Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6604.

Abstract 1397: Metabolic CRISPR-Cas9 screening identifies loss of mitochondriaGene Min triple-negative breast cancer to promote lung metastasis via immune modulation

Abstract Triple-negative breast cancer (TNBC) is a heterogenous breast cancer characterized by an aggressive phenotype and high risk of metastatic occurrence. Metastasis is a multifaceted process that involves metabolic reprogramming, selection, and adaptation. Although studies have shown that alterations of metabolic processes can influence TNBC phenotype and sensitivity to treatments, less is known about how changes in metabolic enzymes in the tumor cells affect crosstalk between tumor and immune cells during metastasis. Here, we performed a high-throughput CRISPR-Cas9 screening of metabolic genes in an orthotopic basal-like mammary carcinoma 4T1 mouse model to identify key metabolic enzymes in the tumor cells that are associated with TNBC lung metastasis by affecting the tumor microenvironment (TME). The CRISPR-Cas9 screening showed an enrichment of sgRNA for mitochondria Gene M in the metastasized lungs of wild-type mice but not Rag1−/− mice, indicating that loss of Gene M could modulate adaptive immune cells in the TME or distant organs to promote 4T1 lung metastasis. Further pilot experiments revealed that loss of Gene M in 4T1 cells increased murine basal-like carcinoma lung metastasis in vivo and decreased population of B cells, CD4+ T cells, M2 macrophages, monocytes, and CXCR2+ neutrophils in the metastasized lungs without affecting the growth rate of the primary tumors. Overall, our preliminary results demonstrated that Gene M deficiency in 4T1 cells affects immune cell profile and drives lung metastasis of murine basal-like carcinoma cells, but the molecular and cellular mechanisms by which loss of Gene M grant tumor cells with metastatic advantage requires further investigation. Citation Format: Shu-Ting Chou, Xiaoyong Wang, Deanna N. Edwards, Jin Chen. Metabolic CRISPR-Cas9 screening identifies loss of mitochondriaGene Min triple-negative breast cancer to promote lung metastasis via immune modulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1397.

Correlation between S100A7 and immune characteristics, methylation, tumor stemness and tumor heterogeneity in pan-cancer and its role in chemotherapy resistance in breast cancer.

To explore the relationships between S100A7 and the immune characteristics, tumor heterogeneity, and tumor stemness pan-cancer as well as the effect of S100A7 on chemotherapy sensitivity in breast cancer. TCGA-BRCA and TCGA-PANCANCER RNA-seq data and clinical follow-up survival data were collected from the University of California Santa Cruz database. Survival analyses were performed to explore the relationship between S100A7 expression and pan-cancer prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and Gene Set Enrichment Analysis (GSEA) were used to identify the potential pathways related to the differentially expressed genes in breast cancer. Spearman's and Wilcoxon's tests were used to investigate the relationships between S100A7 expression and immune characteristics, methylation, tumor heterogeneity, and tumor stemness. The potential functions of S100A7 and its influence on chemotherapy sensitivity in breast cancer were elucidated using reverse transcription-quantitative PCR, Cell Counting Kit-8 (CCK-8) assay, Transwell assay, and wound healing assay. S100A7 was highly expressed in most types of tumors and was associated with poor prognosis. S100A7 was closely associated with immunomodulators, immune checkpoint and immune cell infiltration. Further, S100A7 was related to tumor mutational burden, tumor heterogeneity, methylation and tumor stemness in breast cancer. High S100A7 expression was associated with the invasiveness, migration, proliferation and chemotherapy resistance of breast cancer cells in vitro experiments. High S100A7 expression was related with poor prognosis and chemotherapy resistance in breast cancer, making it a potential immune and chemotherapy resistance biomarker.

Intertumoral heterogeneity of bifocal breast cancer: a morphological and molecular study.

To analyze concordance rates between individual foci of bifocal BC for histological grade, type and intrinsic subtype based on immunohistochemical (IHC) and mRNA-testing using MammaTyper. We evaluated histological grade and type as well as intrinsic subtype based on IHC status for estrogen and progesterone receptors, HER2 and the mitotic activity index in 158 individual foci of 79 bifocal BC. A subgroup of 31 cases additionally underwent mRNA-based subtyping using the MammaTyper (MT) test. We calculated concordance rates between individual foci, as well as Cohen's Kappa (K). For 79 bifocal BC, concordance rates between individual foci for grade, histological type, and IHC-based subtype were 69.6% (K=0.53), 92.4% (K=0.81), and 74.7% (K=0.62), respectively. In the MT subgroup of 31 bifocal BC, concordance rates between individual foci for grade, histological type, IHC-based and mRNA-based intrinsic subtype were 87.1% (K=0.78), 90.3% (K=0.73), 87.1% (K=0.82), and 87.1% (K=0.7), respectively. Overall concordance between IHC- and mRNA-based subtype in the MT subgroup was 79% (K=0.7). In 6/79 cases (7.6%), testing of the smaller focus added clinically relevant information either on IHC- or mRNA-level: four cases showed high hormonal receptor expression while the expression in the larger focus was negative or low, warranting additional endocrine treatment; two cases presented with higher proliferative activity in the smaller focus, warranting additional chemotherapy. In bifocal BC, intertumoral heterogeneity on the morphological, immunohistochemical and molecular level is common, with discordant intrinsic subtype in up to 25% between individual foci, with about 8% clinically relevant discordances.

The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics.

Despite significant progress in the prevention, screening, diagnosis, prognosis, and therapy of breast cancer (BC), it remains a highly prevalent and life-threatening disease affecting millions worldwide. Molecular subtyping of BC is crucial for predictive and prognostic purposes due to the diverse clinical behaviors observed across various types. The molecular heterogeneity of BC poses uncertainties in its impact on diagnosis, prognosis, and treatment. Numerous studies have highlighted genetic and environmental differences between patients from different geographic regions, emphasizing the need for localized research. International studies have revealed that patients with African heritage are often diagnosed at a more advanced stage and exhibit poorer responses to treatment and lower survival rates. Despite these global findings, there is a dearth of in-depth studies focusing on communities in the African region. Early diagnosis and timely treatment are paramount to improving survival rates. In this context, radiogenomics emerges as a promising field within precision medicine. By associating genetic patterns with image attributes or features, radiogenomics has the potential to significantly improve early detection, prognosis, and diagnosis. It can provide valuable insights into potential treatment options and predict the likelihood of survival, progression, and relapse. Radiogenomics allows for visual features and genetic marker linkage that promises to eliminate the need for biopsy and sequencing. The application of radiogenomics not only contributes to advancing precision oncology and individualized patient treatment but also streamlines clinical workflows. This review aims to delve into the theoretical underpinnings of radiogenomics and explore its practical applications in the diagnosis, management, and treatment of BC and to put radiogenomics on a path towards fully integrated diagnostics.

Multi-omics analysis elucidates the relationship between intratumor microbiome and host immune heterogeneity in breast cancer.

Research has indicated that intratumor microbiomes affect the occurrence, progression, and therapeutic response in many cancer types by influencing the immune system. We aim to evaluate the characteristics of immune-related intratumor microbiomes (IRIMs) in breast cancer (BC) and search for potential prognosis prediction factors and treatment targets. The clinical information, microbiome data, transcriptomics data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) patients were obtained from Kraken-TCGA-Raw-Data and TCGA portal. The core tumor-infiltrating immune cell was identified using univariate Cox regression analysis. Based on consensus clustering analysis, BC patients were categorized into two immune subtypes, referred to as immune-enriched and immune-deficient subtypes. The immune-enriched subtype, characterized by higher levels of immune infiltration of CD8+ T and macrophage M1 cells, demonstrated a more favorable prognosis. Furthermore, significant differences in alpha-diversity and beta-diversity were observed between the two immune subtypes, and the least discriminant analysis effect size method identified 33 types of IRIMs. An intratumor microbiome-based prognostic signature consisting of four prognostic IRIMs (Acidibacillus, Succinimonas, Lachnoclostridium, and Pseudogulbenkiania) was constructed using the Cox proportional-hazard model, and it had great prognostic value. The prognostic IRIMs were correlated with immune gene expression and the sensitivity of chemotherapy drugs, specifically tamoxifen and docetaxel. In conclusion, our research has successfully identified two distinct immune subtypes in BC, which exhibit contrasting prognoses and possess unique epigenetic and intratumor microbiomes. The critical IRIMs were correlated with prognosis, tumor-infiltrating immune cell abundance, and immunotherapeutic efficacy in BC. Consequently, this study has identified potential IRIMs as biomarkers, providing a novel therapeutic approach for treating BC.IMPORTANCERecent research has substantiated the presence of the intratumor microbiome in tumor immune microenvironment, which could influence tumor occurrence and progression, as well as provide new opportunities for cancer diagnosis and treatment. This study identified the critical immune-related intratumor microbiome (Acidibacillus, Succinimonas, Lachnoclostridium, and Pseudogulbenkiania), which were correlated with prognosis, tumor-infiltrating immune cell abundance, and immunotherapeutic efficacy in breast cancer and might be the novel target to regulate immunotherapy in BC.

Analyses of hypoxia-related risk factors and clinical relevance in breast cancer.

Hypoxia plays an important role in the heterogeneity, relapse, metastasis, and drug resistance of breast cancer. In this study, we explored the hypoxia-related biological signatures in different subtypes of breast cancer and identified the key prognostic factors by bioinformatics methods. Based on The Cancer Genome Atlas (TCGA) Breast Cancer datasets, we divided the samples into immune-activated/suppressed populations by single-sample gene set enrichment analysis (ssGSEA) and then used hierarchical clustering to further identify hypoxic/non-hypoxic populations from the immune-suppressed samples. A hypoxia related risk model of breast cancer was constructed. Nuclear factor interleukin-3 regulated (NFIL3), serpin family E member 1 (SERPINE1), FOS, biglycan (BGN), epidermal growth factor receptor (EGFR), and sushi-repeat-containing protein, X-linked (SRPX) were identified as key hypoxia-related genes. Margin status, American Joint Committee on Cancer (AJCC) stage, hypoxia status, estrogen receptor/progesterone receptor (ER/PR) status, NFIL3, SERPINE1, EGFR, and risk score were identified as independent prognostic indicators for breast cancer patients. The 3- and 5-year survival curves of the model and immunohistochemical staining on the breast cancer microarray verified the statistical significance and feasibility of our model. Among the different molecular types of breast cancer, ER/PR+ and HER2+ patients might have higher hypoxia-related risk scores. ER/PR-negative samples demonstrated more activated immune-related pathways and better response to most anticancer agents. Our study revealed a novel risk model and potential feasible prognostic factors for breast cancer and might provide new perspectives for individual breast cancer treatment.

Disulfidptosis heterogeneity in breast cancer uncovers PTTG1IP as an actionable therapeutic target

Disulfidptosis heterogeneity in breast cancer uncovers PTTG1IP as an actionable therapeutic target

Few-shot genes selection: subset of PAM50 genes for breast cancer subtypes classification

BackgroundIn recent years, researchers have made significant strides in understanding the heterogeneity of breast cancer and its various subtypes. However, the wealth of genomic and proteomic data available today necessitates efficient frameworks, instruments, and computational tools for meaningful analysis. Despite its success as a prognostic tool, the PAM50 gene signature’s reliance on many genes presents challenges in terms of cost and complexity. Consequently, there is a need for more efficient methods to classify breast cancer subtypes using a reduced gene set accurately.ResultsThis study explores the potential of achieving precise breast cancer subtype categorization using a reduced gene set derived from the PAM50 gene signature. By employing a “Few-Shot Genes Selection” method, we randomly select smaller subsets from PAM50 and evaluate their performance using metrics and a linear model, specifically the Support Vector Machine (SVM) classifier. In addition, we aim to assess whether a more compact gene set can maintain performance while simplifying the classification process. Our findings demonstrate that certain reduced gene subsets can perform comparable or superior to the full PAM50 gene signature.ConclusionsThe identified gene subsets, with 36 genes, have the potential to contribute to the development of more cost-effective and streamlined diagnostic tools in breast cancer research and clinical settings.

Clinical sequencing defines the somatic and germline mutation landscapes of Chinese HER2-Low Breast Cancer

More than half of the breast cancer initially labeled as human epidermal growth factor receptor 2 (HER2)-negative actually exhibited low HER2 levels (IHC 1+ or IHC 2+/FISH-) and were classified as HER2-low breast cancer. Previous research emphasized the significant biological heterogeneity in HER2-low breast cancer, highlighting the importance of accurately characterizing HER2-low tumors to promote the precise management of antibody‒drug conjugates. In this study, we established a large-scale targeted sequencing cohort (N = 1907) representing Chinese HER2-low breast cancer patients with detailed clinical annotation. Our research findings revealed that HER2-low breast cancer demonstrated distinct clinical pathological characteristics and mutation landscapes compared to HER2-zero group. When compared to HER2-zero tumors, HER2-low tumors exhibited a higher proportion of Luminal B subtypes and better disease-free survival. In hormone receptor (HR)-positive breast cancer, HER2-low group showed a higher frequency of GATA3 somatic mutations, BRCA2 germline mutations, and mutations in the DNA damage repair pathway. In contrast, in HR-negative breast cancer, the HER2-low group displayed a higher frequency of PIK3CA mutations and PI3K pathway alterations. These findings offered valuable insights for the precise targeted treatment of HER2-low breast cancer in different HR statuses.

Exploring contemporary breakthroughs in utilizing vesicular nanocarriers for breast cancer therapy.

Breast cancer (BC) is a heterogeneous disease with various morphological features, clinicopathological conditions and responses to different therapeutic options, which is responsible for high mortality and morbidity in women. The heterogeneity of BC necessitates new strategies for diagnosis and treatment, which is possible only by cautious harmonization of the advanced nanomaterials. Recent developments in vesicular nanocarrier therapy indicate a paradigm shift in breast cancer treatment by providing an integrated approach to address current issues. This review provides a detailed classification of various nanovesicles in the treatment of BC with a special emphasis on recent advances, challenges in translating nanomaterialsand future potentials.

High Intensity Focused Ultrasound-Driven Nanomotor for Effective Ferroptosis-Immunotherapy of TNBC.

The heterogeneity of triple-negative breast cancers (TNBC) remains challenging for various treatments. Ferroptosis, a recently identified form of cell death resulting from the unrestrained peroxidation of phospholipids, represents a potential vulnerability in TNBC. In this study, a high intensity focused ultrasound (HIFU)-driven nanomotor is developed for effective therapy of TNBC through induction of ferroptosis. Through bioinformatics analysis of typical ferroptosis-associated genes in the FUSCCTNBC dataset, gambogic acid is identified as a promising ferroptosis drug and loaded it into the nanomotor. It is found that the rapid motion of nanomotors propelled by HIFU significantly enhanced tumor accumulation and penetration. More importantly, HIFU not only actuated nanomotors to trigger effective ferroptosis of TNBC cells, but also drove nanomotors to activate ferroptosis-mediated antitumor immunity in primary and metastatic TNBC models, resulting in effective tumor regression and prevention of metastases. Overall, HIFU-driven nanomotors show great potential for ferroptosis-immunotherapy of TNBC.

Hypofunction of macrophage chemotaxis contributes to defective efficacy of herceptin in HER2-positive breast cancer patients

ABSTRACT Breast cancer was considered as a kind of prone breast tumors with the complicated pathological mechanisms and diverse clinical classifications. In the clinical treatments of HER2-positive tumor patients, HER2 monoclonal antibodies, such as Herceptin, have shown well-defined therapeutic effects. Nevertheless, due to the heterogeneity of breast cancers, drug resistance inevitably appeared during the application of Herceptin. In order to fully understand the immune tolerance status of the tumor microenvironment in the population of sensitive and insensitive patients, this study carried out a series of studies through Luminex cytokines assay, clinicopathological analysis, immunofluorescence, and PCR. The results confirmed that in clinical samples sensitive to Herceptin, there were a large number of macrophages, and the protein expression levels and in situ expression of macrophage-related chemokines and inflammatory mediators are significantly higher than drug-resistant tumor samples. Further studies found that T cell function has a low correlation with tumor growth, and there are obvious obstacles in the process of peripheral blood immune cells entering the tumor microenvironment. In summary, this study provided clues for understanding the clinical drug resistance of HER2 monoclonal antibody and the clinical rational use of drugs and combination drugs.

An analysis of the prognostic role of reactive oxygen species-associated genes in breast cancer.

This study aimed to type breast cancer in relation to reactive oxygen species (ROS), clinical indicators, single nucleotide variant (SNV) mutations, functional differences, immune infiltration, and predictive responses to immunotherapy or chemotherapy, and constructing a prognostic model. We used uniCox analysis, ConsensusClusterPlus, and the proportion of ambiguous clustering (PAC) to analyze The Cancer Genome Atlas (TCGA) data to determine optimal groupings and obtain differentially expressed ROS-related genes. Clinical indicators were then combined with the classification results and the Chi-square test was used to assess differences. We further examined SNV mutations, and functional differences using gene set enrichment analysis (GSEA) analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, immune cell infiltration, and response to immunotherapy and chemotherapy. A prognostic model for breast cancer was constructed using these differentially expressed genes, immunotherapy or chemotherapy responses, and survival curves. RT-qPCR was used to detect the differences in the expression of LCE3D, CA1, PIRT and SMR3A in breast cancer cell lines and normal breast epithelial cell line. We identified two distinct tumor types with significant differences in ROS-related gene expression, clinical indicators, SNV mutations, functional pathways, and immune infiltration. The response to specific chemotherapy drugs and immunotherapy treatments also documented significant differences. The prognostic model constructed with 16 genes linked to survival could efficiently divide patients into high- and low-risk groups. The high-risk group showed a poorer prognosis, higher tumor purity, distinct immune microenvironment, and lower immunotherapy response. RT-qPCR results showed that LCE3D, CA1, PIRT and SMR3A are highly expressed in breast cancer. Our methodical examination presented an enhanced insight into the molecular and immunological heterogeneity of breast cancer. It can contribute to the understanding of prognosis and offer valuable insights for personalized treatment strategies. Further, the prognostic model can potentially serve as a powerful tool for risk stratification and therapeutic decision-making in clinical settings.

Abstract A062: Somatic engineering of rat models to recapitulate human breast cancer evolution and heterogeneity

Abstract Estrogen receptor (ER) positive breast cancer accounts for over 75% of all presenting clinical cases. In addition, almost all Ductal Carcinoma in situ (DCIS) lesions, now accounting for about 25% of all newly diagnosed ‘breast cancers’, are ER-dependent. Despite the high occurrence, the molecular underpinnings regulating DCIS initiation and progression to invasive disease remain elusive. This gap in knowledge is primarily due to the dearth of suitable preclinical models that accurately emulate breast cancer heterogeneity. To overcome this impediment, we developed a platform of somatic models by engineering the rat mammary gland and manipulating the genes most frequently mutated in hormone-dependent (pre-)breast cancer. This has successfully led to the generation of ER-positive disease models that provide a nuanced understanding of ER functionality and the complex mechanisms of ER signaling, which we show to be dependent on the cancer genotype. This has potential implications for the formulation of innovative endocrine therapy treatment regimens. Our models have generated an array of tumor types, including ductal and lobular carcinomas, manifesting both in situ and invasive phenotypes, faithfully recapitulating human breast disease and the evolution of tumorigenesis. Intriguingly, our results indicate how different oncogenic mutations modulate not only the architectural and histopathological characteristics of cancer but also the immune microenvironment, thereby generating possibilities for future therapeutic testing. Our research augments the range of available ER-positive in situ and invasive breast cancer models, benefitting the stratification of indolent from aggressive disease and facilitating the exploration of novel treatment strategies for this pervasive breast cancer subtype. Citation Format: Catrin Lutz, Ji-Ying Song, Hendrik A Messal, Madelon Badoux, Timo Eijkman, Bim de Klein, Jelle Wesseling, Jos Jonkers. Somatic engineering of rat models to recapitulate human breast cancer evolution and heterogeneity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A062.