Breast Tumor Microenvironment Research Articles

An insight into the role of innate immune cells in breast tumor microenvironment.

The immune background of breast cancer is highly heterogeneous and the immune system of the human body plays a dual role by both promoting and suppressing its progression. Innate immune cells are the first line of defense in the immune system and impart protection by identifying and interacting with foreign pathogens and cancer cells. Different innate immune cells like natural killer cells, macrophages, dendritic cells, and myeloid suppressor cells take part in hosting the cancer cells. Autophagy is another key component inside the tumor microenvironment and is linked to the disintegration and recycling of cellular components. Within the tumor microenvironment autophagy is involved with Pattern Recognition Receptors and inflammation. Various clinical studies have shown prominent results where innate immune cells and autophagy in combination are used for pathogen as well as cancer cell clearance. However, it is necessary to comprehend the complex tumor microenvironment so that different therapeutic approaches can be developed to enhance the suppressive actions of the cells toward breast cancer cells. In this review article, the complex interaction between immune cells and breast cancer cells and their role in developing effective immunotherapies to improve patient outcomes are discussed in detail.

Systemic and local chronic inflammation and hormone disposition promote a tumor-permissive environment for breast cancer in older women.

We uncover the unique underpinnings establishing how the systemic host environment contributes to the aged breast tumor microenvironment, characterized by high local estradiol and chronic inflammation with immune dysregulation, and show that targeting avenues of estrogen conversion and chronic inflammation work to restore anti-tumor immunity.

Rational Design of HER2-Targeted Combination Therapies to Reverse Drug Resistance in Fibroblast-Protected HER2+ Breast Cancer Cells

Abstract Introduction Fibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells. Methods Drug sensitivity to the HER2 kinase inhibitor lapatinib was characterized under conditions of monoculture and exposure to breast fibroblast-conditioned medium. Protein expression was measured using reverse phase protein arrays. Candidate targets for combination therapy were identified using differential expression and multivariate regression modeling. Follow-up experiments were performed to evaluate the effects of HER2 kinase combination therapies in fibroblast-protected cancer cell lines and fibroblasts. Results Compared to monoculture, fibroblast-conditioned medium increased the expression of plasminogen activator inhibitor-1 (PAI1) and cell cycle regulator polo like kinase 1 (PLK1) in lapatinib-treated breast cancer cells. Combination therapy of lapatinib with inhibitors targeting either PAI1 or PLK1, eliminated fibroblast-protected cancer cells, under both conditions of direct coculture with fibroblasts and protection by fibroblast-conditioned medium. Analysis of publicly available, clinical transcriptomic datasets revealed that HER2-targeted therapy fails to suppress PLK1 expression in stroma-rich HER2+ breast tumors and that high PAI1 gene expression associates with high stroma density. Furthermore, we showed that an epigenetics-directed approach using a bromodomain and extraterminal inhibitor to globally target fibroblast-induced proteomic adaptions in cancer cells, also restored lapatinib sensitivity. Conclusions Our data-driven framework of proteomic profiling in breast cancer cells identified the proteolytic degradation regulator PAI1 and the cell cycle regulator PLK1 as predictors of fibroblast-mediated treatment resistance. Combination therapies targeting HER2 kinase and these fibroblast-induced signaling adaptations eliminates fibroblast-protected HER2+ breast cancer cells.

8398 Non-genomic Effects of Thyroid Hormones on the Breast Cancer Microenvironment

Abstract Disclosure: L. Drago: None. S. Shahrivari: None. N. Schwenk: None. P. Nelson: None. H. Hosseini: None. C. Spitzweg: None. Objective: Mesenchymal stem cells (MSCs) are central players in the genesis of the breast cancer tumor microenvironment and play a role in tumor initiation, progression, invasion, metastasis, angiogenesis as well as resistance to treatment. There is increasing evidence for an association between thyroid function and breast cancer risk. Thyroid hormone effects mediated through the αvβ3 integrin, a thyroid hormone receptor, are proposed as a pathophysiologic link to this observation. Methods: To evaluate the migratory behavior of MSCs in the presence or absence of thyroid hormone treatment in response to tumor-derived signals, a 3D migration assay was performed. MSCs pretreated with T3 (1nM) or T4 (1μM) with or without tetrac (100nM) (T4 analog, specific inhibitor of αvβ3 integrin-mediated thyroid hormone action) for 24 h were subjected to a gradient between serum-free medium and serum-free conditioned medium (CM) from five different breast cancer cell lines representative of different breast cancer subtypes including T47D as Luminal B, MCF7 as Luminal A, BT-474 and MDA-MB-453 as HER2, and MDA-MB-231 as Triple negative subtype. Results: MSCs subjected to a gradient between CM derived from each breast cancer cell line and serum-free medium showed directed chemotaxis towards tumor-CM with a significantly increased forward migration index (FMI) and center of mass (CoM). This migratory behavior was significantly enhanced upon treatment with T3 or T4. The cellular migration towards tumor-CM of MDA-MB-453, BT-474, and T47D was more effective upon MSC treatment with T3, but less so with T4. MSCs treated with T4 showed a better migratory performance towards the CM of MCF7 and MDA-MB-231. Except for T47D-CM, additional treatment with tetrac inhibited the enhanced effects of T3 and T4 on MSC migration demonstrating that this effect is mediated through αvβ3 integrin. Conclusion: Our preliminary in vitro data on the effects of thyroid hormones T3 and T4, and the thyroid hormone metabolite tetrac on MSC migration shows a distinct behaviour of MSCs in the presence of either T3 or T4 depending on the breast cancer cell subtype, suggesting a role of non-genomic, integrin αvβ3-mediated thyroid hormone action on MSC biology within the breast tumor microenvironment that warrants further investigation. Presentation: 6/3/2024

8398 Non-genomic Effects Of Thyroid Hormones On The Breast Cancer Microenvironment

Abstract Disclosure: L. Drago: None. S. Shahrivari: None. N. Schwenk: None. P. Nelson: None. H. Hosseini: None. C. Spitzweg: None. Objective: Mesenchymal stem cells (MSCs) are central players in the genesis of the breast cancer tumor microenvironment and play a role in tumor initiation, progression, invasion, metastasis, angiogenesis as well as resistance to treatment. There is increasing evidence for an association between thyroid function and breast cancer risk. Thyroid hormone effects mediated through the αvβ3 integrin, a thyroid hormone receptor, are proposed as a pathophysiologic link to this observation. Methods: To evaluate the migratory behavior of MSCs in the presence or absence of thyroid hormone treatment in response to tumor-derived signals, a 3D migration assay was performed. MSCs pretreated with T3 (1nM) or T4 (1μM) with or without tetrac (100nM) (T4 analog, specific inhibitor of αvβ3 integrin-mediated thyroid hormone action) for 24 h were subjected to a gradient between serum-free medium and serum-free conditioned medium (CM) from five different breast cancer cell lines representative of different breast cancer subtypes including T47D as Luminal B, MCF7 as Luminal A, BT-474 and MDA-MB-453 as HER2, and MDA-MB-231 as Triple negative subtype. Results: MSCs subjected to a gradient between CM derived from each breast cancer cell line and serum-free medium showed directed chemotaxis towards tumor-CM with a significantly increased forward migration index (FMI) and center of mass (CoM). This migratory behavior was significantly enhanced upon treatment with T3 or T4. The cellular migration towards tumor-CM of MDA-MB-453, BT-474, and T47D was more effective upon MSC treatment with T3, but less so with T4. MSCs treated with T4 showed a better migratory performance towards the CM of MCF7 and MDA-MB-231. Except for T47D-CM, additional treatment with tetrac inhibited the enhanced effects of T3 and T4 on MSC migration demonstrating that this effect is mediated through αvβ3 integrin. Conclusion: Our preliminary in vitro data on the effects of thyroid hormones T3 and T4, and the thyroid hormone metabolite tetrac on MSC migration shows a distinct behaviour of MSCs in the presence of either T3 or T4 depending on the breast cancer cell subtype, suggesting a role of non-genomic, integrin αvβ3-mediated thyroid hormone action on MSC biology within the breast tumor microenvironment that warrants further investigation. Presentation: 6/3/2024

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

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

Alginate-functionalized and 4T1 cell membrane-coated multi-tasking nanoparticulate system for near-infrared-triggered photodynamic therapy on breast cancer: In vitro cellular and in vivo mice models

Recently, combination treatment of chemo-dynamic therapy (CDT) and photodynamic therapies (PDT) is well-known and prominent therapeutic strategy for breast tumor. Importantly, tailored nanomedicines with unique personalized properties including nanocarrier suitability and effective targeting ability that requires the exhaustive understanding of tumor microenvironment. Recently, researchers have designed a smart upconversion nanoparticles (UCNPs) that have unique characteristics to achieve targeting for respond tumor microenvironment. In the present study, we first time fabricated a novel combination of oxidized sodium alginate-enveloped and 4T1 cancer cell membrane-coated up-conversion nanoparticles (4TUCNP@SMZ) were engineered for breast cancer-targeted therapy. The nanoparticles could be formed via electrostatic interaction, which showed excellent biocompatibility, increased cellular uptake with normal and cancer cells. The fabricated Alginate and 4T1-membrane functionalized up-conversion nanoparticles significantly benefitted to targeted delivery system for local breast cancer and prominently inhibit tumor development via chemo-dynamic therapy (CDT) and PDT. The greater susceptibility of tumor cells to oxidative stress may also result from the depletion of intracellular GSH by the 4TUCNP@SMZ nanoparticles. The in vitro cell models (4T1 and MCF-7), in vivo tumor model and histological observation demonstrated that 4TUCNP@SMZ nanoparticles effectively targeted to breast tumor microenvironment and inhibit breast cancer cells. This report suggested that multifunctional Alginate-functionalized nanoparticles are a versatile agent for phototherapy for breast cancer treatment.

Reprogramming of breast tumor-associated macrophages with modulation of arginine metabolism.

HER2+ breast tumors have abundant immune-suppressive cells, including M2-type tumor-associated macrophages (TAMs). Although TAMs consist of the immune-stimulatory M1 type and immune-suppressive M2 type, the M1/M2-TAM ratio is reduced in immune-suppressive tumors, contributing to their immunotherapy refractoriness. M1- versus M2-TAM formation depends on differential arginine metabolism, where M1-TAMs convert arginine to nitric oxide (NO) and M2-TAMs convert arginine to polyamines (PAs). We hypothesize that such distinct arginine metabolism in M1- versus M2-TAMs is attributed to different availability of BH4 (NO synthase cofactor) and that its replenishment would reprogram M2-TAMs to M1-TAMs. Recently, we reported that sepiapterin (SEP), the endogenous BH4 precursor, elevates the expression of M1-TAM markers within HER2+ tumors. Here, we show that SEP restores BH4 levels in M2-like macrophages, which then redirects arginine metabolism to NO synthesis and converts M2 type to M1 type. The reprogrammed macrophages exhibit full-fledged capabilities of antigen presentation and induction of effector T cells to trigger immunogenic cell death of HER2+ cancer cells. This study substantiates the utility of SEP in the metabolic shift of the HER2+ breast tumor microenvironment as a novel immunotherapeutic strategy.

Obesity, dysbiosis and inflammation: interactions that modulate the efficacy of immunotherapy.

Recent years have seen an outstanding growth in the understanding of connections between diet-induced obesity, dysbiosis and alterations in the tumor microenvironment. Now we appreciate that gut dysbiosis can exert important effects in distant target tissues via specific microbes and metabolites. Multiple studies have examined how diet-induced obese state is associated with gut dysbiosis and how gut microbes direct various physiological processes that help maintain obese state in a bidirectional crosstalk. Another tightly linked factor is sustained low grade inflammation in tumor microenvironment that is modulated by both obese state and dysbiosis, and influences tumor growth as well as response to immunotherapy. Our review brings together these important aspects and explores their connections. In this review, we discuss how obese state modulates various components of the breast tumor microenvironment and gut microbiota to achieve sustained low-grade inflammation. We explore the crosstalk between different components of tumor microenvironment and microbes, and how they might modulate the response to immunotherapy. Discussing studies from multiple tumor types, we delve to find common microbial characteristics that may positively or negatively influence immunotherapy efficacy in breast cancer and may guide future studies.

Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells.

Metastasis is responsible for the majority of cancer-related fatalities. We previously identified specific cancer cell populations responsible for metastatic events which are cytokeratin-14 (CK14) and E-cadherin positive in luminal tumors, and E-cadherin and vimentin positive in triple-negative tumors. Since cancer cells evolve within a complex ecosystem comprised of immune cells and stromal cells, we sought to decipher the spatial interactions of these aggressive cancer cell populations within the tumor microenvironment (TME). We used imaging mass cytometry to detect 36 proteins in tumor microarrays containing paired primary and metastatic lesions from luminal or triple-negative breast cancers (TNBC), resulting in a dataset of 1,477,337 annotated cells. Focusing on metastasis-initiating cell populations, we observed close proximity to specific fibroblast and macrophage subtypes, a relationship maintained between primary and metastatic tumors. Notably, high CK14 in luminal cancer cells and high vimentin in TNBC cells correlated with close proximity to specific macrophage subtypes (CD163intCD206intPDL1intHLA-DR+ or PDL1highARG1high). Our in-depth spatial analysis demonstrates that metastasis-initiating cancer cells consistently colocalizes with distinct cell populations within the TME, suggesting a role for these cell-cell interactions in promoting metastasis.

Infiltration of Common Myeloid Progenitor (CMP) Cells is Associated With Less Aggressive Tumor Biology, Lower Risk of Brain Metastasis, Better Response to Immunotherapy, and Higher Patient Survival in Breast Cancer.

To investigate the clinical relevance of common myeloid progenitor (CMP) cells in breast tumor microenvironment (TME). The role of rare cells in TME is less studied. In Silico transcriptomic analyses of real-world data enable us to detect and quantify rare cells, including CMP cells. A total of 5176 breast cancer (BC) patients from SCAN-B, METABRIC, and 5 single-cell sequence cohorts were analyzed using the xCell algorithm. The high group was defined as more than two-thirds of the CMP scores in each cohort. CMP cells consist of 0.07% to 0.25% of bulk breast tumor cells, more in estrogen receptor-positive (ER+) compared with triple-negative (TN) subtype (0.1% to 0.75%, 0.18% to 0.33% of immune cells, respectively). CMP cells did not correlate with any of the myeloid lineages or stem cells in TME. CMP infiltration was higher in smaller tumors, with lower Nottingham grade, and in ER+/HER2- than in TNBC consistently in both SCAN-B and METABRIC cohorts. High CMP was significantly associated with a lower risk of brain metastasis and with better survival, particularly in ER+/HER2-. High CMP enriched epithelial-to-mesenchymal transition and angiogenesis pathways, and less cell proliferation and DNA repair gene sets. High CMP ER+/HER2- was associated with less immune cell infiltration and cytolytic activity ( P <0.001). CMP infiltration correlated with neoadjuvant chemoimmunotherapy response for both ER+/HER2- and TNBC in the ISPY-2 cohort (AUC=0.69 and 0.74, respectively). CMP in BC is inversely associated with cell proliferation and brain metastasis, better response to immunotherapy, and survival. This is the first to report the clinical relevance of CMP infiltration in BC.

A panoptic segmentation dataset and deep-learning approach for explainable scoring of tumor-infiltrating lymphocytes

Tumor-Infiltrating Lymphocytes (TILs) have strong prognostic and predictive value in breast cancer, but their visual assessment is subjective. To improve reproducibility, the International Immuno-oncology Working Group recently released recommendations for the computational assessment of TILs that build on visual scoring guidelines. However, existing resources do not adequately address these recommendations due to the lack of annotation datasets that enable joint, panoptic segmentation of tissue regions and cells. Moreover, existing deep-learning methods focus entirely on either tissue segmentation or cell nuclei detection, which complicates the process of TILs assessment by necessitating the use of multiple models and reconciling inconsistent predictions. We introduce PanopTILs, a region and cell-level annotation dataset containing 814,886 nuclei from 151 patients, openly accessible at: sites.google.com/view/panoptils. Using PanopTILs we developed MuTILs, a neural network optimized for assessing TILs in accordance with clinical recommendations. MuTILs is a concept bottleneck model designed to be interpretable and to encourage sensible predictions at multiple resolutions. Using a rigorous internal-external cross-validation procedure, MuTILs achieves an AUROC of 0.93 for lymphocyte detection and a DICE coefficient of 0.81 for tumor-associated stroma segmentation. Our computational score closely matched visual scores from 2 pathologists (Spearman R = 0.58–0.61, p < 0.001). Moreover, computational TILs scores had a higher prognostic value than visual scores, independent of TNM stage and patient age. In conclusion, we introduce a comprehensive open data resource and a modeling approach for detailed mapping of the breast tumor microenvironment.

Macrophage-conditioned medium enhances tunneling nanotube formation in breast cancer cells via PKC, Src, NF-κB, and p38 MAPK signaling

Tumor-associated macrophages (TAMs) secrete cytokines, chemokines, and growth factors in the tumor microenvironment (TME) to support cancer progression. Higher TAM infiltration in the breast TME is associated with a poor prognosis. Previous studies have demonstrated the role of macrophages in stimulating long-range intercellular bridges referred to as tunneling nanotubes (TNTs) in cancer cells. Intercellular communication between cancer cells via TNTs promotes cancer growth, invasion, metastasis, and therapy resistance. Given the important role of TNTs and macrophages in cancer, the role of macrophage-induced TNTs in chemotherapy drug doxorubicin resistance is not known. Furthermore, the mechanism of macrophage-mediated TNT formation is elusive. In this study, it is shown that the macrophage-conditioned medium (MΦCM) partially mimicked inflammatory TME, induced an EMT phenotype, and increased migration in MCF-7 breast cancer cells. Additionally, secreted proteins in MΦCM induced TNT formation in MCF-7 cells, which led to increased resistance to doxorubicin. Transcriptomic analysis of MΦCM-treated MCF-7 cells showed enrichment of the NF-κB and focal adhesion pathways, as well as upregulation of genes involved in EMT, extracellular remodeling, and actin cytoskeleton reorganization. Interestingly, inhibitors of PKC, Src, NF-κB, and p38 decreased macrophage-induced TNT formation in MCF-7 cells. These results reveal the novel role of PKC and Src in inducing TNT formation in cancer cells and suggest that inhibition of PKC and Src activity may likely contribute to reduced macrophage-breast cancer cell interaction and the potential therapeutic strategy of cancer.

Autophagy as a Therapeutic Target in Breast Tumors: The Cancer stem cell perspective.

Breast cancer is a heterogeneous disease, with a subpopulation of tumor cells known as breast cancer stem cells (BCSCs) with self-renewal and differentiation abilities that play a critical role in tumor initiation, progression, and therapy resistance. The tumor microenvironment (TME) is a complex area where diverse cancer cells reside creating a highly interactive environment with secreted factors, and the extracellular matrix. Autophagy, a cellular self-digestion process, influences dynamic cellular processes in the tumor TME integrating diverse signals that regulate tumor development and heterogeneity. Autophagy acts as a double-edged sword in the breast TME, with both tumor-promoting and tumor-suppressing roles. Autophagy promotes breast tumorigenesis by regulating tumor cell survival, migration and invasion, metabolic reprogramming, and epithelial-mesenchymal transition (EMT). BCSCs harness autophagy to maintain stemness properties, evade immune surveillance, and resist therapeutic interventions. Conversely, excessive, or dysregulated autophagy may lead to BCSC differentiation or cell death, offering a potential avenue for therapeutic exploration. The molecular mechanisms that regulate autophagy in BCSCs including the mammalian target of rapamycin (mTOR), AMPK, and Beclin-1 signaling pathways may be potential targets for pharmacological intervention in breast cancer. This review provides a comprehensive overview of the relationship between autophagy and BCSCs, highlighting recent advancements in our understanding of their interplay. We also discuss the current state of autophagy-targeting agents and their preclinical and clinical development in BCSCs.

Spatial N-glycomics of the normal breast microenvironment reveals fucosylated and high-mannose N-glycan signatures related to BI-RADS density and ancestry.

Higher breast cancer mortality rates continue to disproportionally affect black women (BW) compared to white women (WW). This disparity is largely due to differences in tumor aggressiveness that can be related to distinct ancestry-associated breast tumor microenvironments (TMEs). Yet, characterization of the normal microenvironment (NME) in breast tissue and how they associate with breast cancer risk factors remains unknown. N-glycans, a glucose metabolism-linked post-translational modification, has not been characterized in normal breast tissue. We hypothesized that normal female breast tissue with distinct Breast Imaging and Reporting Data Systems (BI-RADS) categories have unique microenvironments based on N-glycan signatures that varies with genetic ancestries. Profiles of N-glycans were characterized in normal breast tissue from BW (n=20) and WW (n=20) at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). A total of 176 N-glycans (32 core-fucosylated and 144 noncore-fucosylated) were identified in the NME. We found that certain core-fucosylated, outer-arm fucosylated and high-mannose N-glycan structures had specific intensity patterns and histological distributions in the breast NME dependent on BI-RADS densities and ancestry. Normal breast tissue from BW, and not WW, with heterogeneously dense breast densities followed high-mannose patterns as seen in invasive ductal and lobular carcinomas. Lastly, lifestyles factors (e.g. age, menopausal status, Gail score, BMI, BI-RADS) differentially associated with fucosylated and high-mannose N-glycans based on ancestry. This study aims to decipher the molecular signatures in the breast NME from distinct ancestries towards improving the overall disparities in breast cancer burden.

Advanced co-culture 3D breast cancer model to study cell death and nanodrug sensitivity of tumor spheroids

The interaction between tumor cells and other cells in the tumor microenvironment (TME) dramatically affects the behavior and progression of the disease. Fibroblasts, as a major component of TME, play a role in cancer development and drug resistance. The current study demonstrates a microfluidic-based co-culture 3D breast cancer spheroids with simplified on-chip testing. To better mimic the breast TME, we have successfully generated a 3D stroma-rich in vitro model of breast cancer using fibroblasts and breast cancer cells. Using fluorescence imaging and histology techniques, the developed spheroids were characterized. MDA-MB-231 cells were successfully grown into 3D spheroids. Upon co-culturing the cells, a decrease in spheroid diameter was detected. Furthermore, tumor spheroids' overall viability was increased when co-cultured with fibroblasts over 5 days. The results demonstrated an increase in ECM content in co-culture spheroids (heterotypic spheroids) compared to mono-culture spheroids (homotypic spheroids), as demonstrated by the augmentation in the quantity of blue stain all over the spheroids. When exposed to liposomal doxorubicin nanodrug, a survival advantage was noticed in heterotypic spheroids compared to mono-culture spheroids (91 % vs. 82 %). The results highlighted the significance of using 3D tumor models rather than 2D systems as a realistic platform for proper evaluation of therapeutics efficacy. The co-culture tumor spheroids in proposed microwell-based microfluidic devices may be valuable to investigate TME and drug screening.

Prognostic Significance of CD163+ and/or CD206+ Tumor-Associated Macrophages Is Linked to Their Spatial Distribution and Tumor-Infiltrating Lymphocytes in Breast Cancer.

Tumor-associated macrophages (TAMs) is a key element in the breast tumor microenvironment. CD163 and CD206 have been utilized for TAM identification, but the clinical implications of TAMs identified by these markers have not been thoroughly explored. This study conducted a comparative analysis of CD163 and CD206 TAMs using digital image analysis, focusing on their spatial distribution and prognostic significance in relation to tumor-infiltrating lymphocytes (TILs). Distinct clinico-pathological and prognostic characteristics were noted between the two types of TAMs. CD163 TAMs were linked to high-grade tumors (p = 0.006), whereas CD206 TAMs were associated with a higher incidence of nodal metastasis (p = 0.033). CD206 TAMs were predominantly found in the stroma, with more cases being stromal CD206-high (sCD206-high) than tumoral CD206-high (tCD206-high) (p = 0.024). Regarding prognostication, patients stratified according to stromal and tumoral densities of CD163 showed different disease-free survival (DFS) time. Specifically, those that were sCD163-low but tCD163-high exhibited the poorest DFS (chi-square = 10.853, p = 0.013). Furthermore, a high sCD163-to-stromal-TILs ratio was identified as an independent predictor of unfavorable survival outcomes (DFS: HR = 3.477, p = 0.018). The spatial distribution and interactions with TILs enhanced the prognostic value of CD163 TAMs, while CD206 TAMs appeared to have limited prognostic utility in breast cancer cases.

Guardians and Mediators of Metastasis: Exploring T Lymphocytes, Myeloid-Derived Suppressor Cells, and Tumor-Associated Macrophages in the Breast Cancer Microenvironment.

Breast cancers (BCs) are solid tumors composed of heterogeneous tissues consisting of cancer cells and an ever-changing tumor microenvironment (TME). The TME includes, among other non-cancer cell types, immune cells influencing the immune context of cancer tissues. In particular, the cross talk of immune cells and their interactions with cancer cells dramatically influence BC dissemination, immunoediting, and the outcomes of cancer therapies. Tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs) represent prominent immune cell populations of breast TMEs, and they have important roles in cancer immunoescape and dissemination. Therefore, in this article we review the features of TILs, TAMs, and MDSCs in BCs. Moreover, we highlight the mechanisms by which these immune cells remodel the immune TME and lead to breast cancer metastasis.

Prospective evaluation of the breast microbiome and tumor microenvironment-related biomarkers of response to neoadjuvant systemic therapy in triple negative breast cancer.

TPS615 Background: Predictive biomarkers of response to combination chemotherapy and immune-checkpoint inhibitors are urgently needed to tailor treatment recommendations for patients with early-stage triple negative breast cancer (eTNBC). Our group has demonstrated that tumour-associated microbiota in primary breast tumours represent promising and novel candidate biomarkers for patients with breast cancer. We aim to prospectively interrogate the breast cancer microbiome and tumour microenvironment (TME) of eTNBC treated with neoadjuvant chemo-immunotherapy, and correlate with clinical outcome. Methods: Trial design: This prospective translational biomarker study is enrolling patients with eTNBC suitable for standard neoadjuvant systemic therapy followed by definitive surgery. The primary objective is to evaluate the change in breast cancer microbiome composition pre- and post-therapy. Secondary objectives include correlation of the breast microbiome with pathologic complete response (pCR) and survival outcomes, tumor infiltrating lymphocytes (TILs), PDL-1 and immune subset analysis, extracellular vesicles analysis and analysis of gut microbiome. Tumor tissue samples will be collected at baseline (mandatory research biopsy) and at the time of surgery. Microbiome evaluation will be conducted using metagenomic sequencing to assess changes in the relative abundance of microbial taxa. Blood and stool samples will be collected and analysed at baseline, on-treatment, at the time of surgery and post-operatively for secondary endpoints. Statistical analysis: Hierarchical clustering of samples based on relative abundance of the operational taxonomic units (OTUs) with sample composition at family and genus level will be performed. Alpha Diversity (Shannon Diversity Index) and Beta Diversity (Jaccard Similarity Index) will be analysed. Principal component analysis (PCA) and Random Forest analysis will be performed for classification and clustering analysis. Comparison of taxa or functions between clinical cohorts will be performed (two tailed Z test) and corrected using the false discovery rate to determine Q-values. Thirty patients will be recruited over 18-24 months. Current status: This University College Cork sponsored trial received ethics approval from the CREC in January 2024 and recruitment is ongoing. Those interested can contact uccctg@ucc.ie. This trial will provide a deeper insight into the potential role of the local breast microbiome as a predictive biomarker for response to neoadjuvant therapy in patients with eTNBC. The results will guide further studies exploring optimal immunomodulatory combinations for the treatment of TNBC and may provide evidence regarding future therapeutic targeting of the breast cancer microbiome.

Epigenetics, Microbiota, and Breast Cancer: A Systematic Review.

Breast cancer is the most frequently diagnosed cancer in women worldwide. According to recent studies, alterations in the microbiota and epigenetic modulations are risk factors for this disease. This systematic review aims to determine the possible associations between the intestinal and mammary microbial populations, epigenetic modifications, and breast cancer. To achieve this objective, we conducted a literature search in the PubMed, Web of Science, and Science Direct databases following the PRISMA guidelines. Although no results are yet available in humans, studies in mice suggest a protective effect of maternal dietary interventions with bioactive compounds on the development of breast tumors in offspring. These dietary interventions also modified the gut microbiota, increasing the relative abundance of short-chain fatty acid-producing taxa and preventing mammary carcinogenesis. In addition, short-chain fatty acids produced by the microbiota act as epigenetic modulators. Furthermore, some authors indicate that stress alters the gut microbiota, promoting breast tumor growth through epigenetic and gene expression changes in the breast tumor microenvironment. Taken together, these findings show the ability of epigenetic modifications and alterations of the microbiota associated with environmental factors to modulate the development, aggressiveness, and progression of breast cancer.