Unveiling the Immune Microenvironment's Role in Breast Cancer: A Glimpse into Promising Frontiers

Unleashing nanotechnology to redefine tumor-associated macrophage dynamics and non-coding RNA crosstalk in breast cancer

Breast cancer is a significant global health issue. Tumor-associated macrophages (TAMs) are crucial in influencing the tumor microenvironment and the progression of the disease. TAMs exhibit remarkable plasticity in adopting distinct phenotypes ranging from pro-inflammatory and anti-tumorigenic (M1-like) to immunosuppressive and tumor-promoting (M2-like). This review elucidates the multifaceted roles of TAMs in driving breast tumor growth, angiogenesis, invasion, and metastatic dissemination. Significantly, it highlights the intricate crosstalk between TAMs and non-coding RNAs (ncRNAs), including microRNAs, long noncoding RNAs, and circular RNAs, as a crucial regulatory mechanism modulating TAM polarization and functional dynamics that present potential therapeutic targets. Nanotechnology-based strategies are explored as a promising approach to reprogramming TAMs toward an anti-tumor phenotype. Various nanoparticle delivery systems have shown potential for modulating TAM polarization and inhibiting tumor-promoting effects. Notably, nanoparticles can deliver ncRNA therapeutics to TAMs, offering unique opportunities to modulate their polarization and activity.

The future of interleukin gene therapy in head and neck cancers

INTRODUCTION

Head and neck cancer (HNC), primarily head and neck squamous cell carcinomas, originates from the squamous epithelium in areas like the oral cavity, lip, larynx, and oropharynx. With high morbidity impacting critical functions, combined treatments like surgery, radiation, and chemotherapy often fall short in advanced stages, highlighting the need for innovative therapies.

AREAS COVERED

This review critically evaluates interleukin (IL) gene therapy for treating HNC. The discussion extends to key ILs in HNC, various gene therapy techniques and delivery methods. We particularly focus on the application of IL-2, IL-12, and IL-24 gene therapies, examining their mechanisms and outcomes in preclinical studies and clinical trials. The final sections address IL gene therapy challenges in HNC, exploring solutions and critically assessing future therapeutic directions.

EXPERT OPINION

Despite advancements in genomic and immunotherapy, significant challenges in HNC treatment persist, primarily due to the immunosuppressive nature of the tumor microenvironment and the adverse effects of current therapies. The therapeutic efficacy of IL gene therapy hinges on overcoming these hurdles through refined delivery methods that ensure targeted, tumor-specific gene expression. Future strategies should focus on refining gene delivery methods and combining IL gene therapy with other treatments to optimize efficacy and minimize toxicity.

Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions

Interactions between cancer cells and immune cells in the tumor microenvironment influence tumor growth and can contribute to the response to cancer immunotherapies. It is difficult to gain mechanistic insights into the effects of cell-cell interactions in tumors using a purely experimental approach. However, computational modeling enables quantitative investigation of the tumor microenvironment, and agent-based modeling, in particular, provides relevant biological insights into the spatial and temporal evolution of tumors. Here, we develop a novel agent-based model (ABM) to predict the consequences of intercellular interactions. Furthermore, we leverage our prior work that predicts the transitions of CD8+ T cells from a naïve state to a terminally differentiated state using Boolean modeling. Given the details incorporated to predict T cell state, we apply the integrated Boolean-ABM framework to study how the properties of CD8+ T cells influence the composition and spatial organization of tumors and the efficacy of an immune checkpoint blockade. Overall, we present a mechanistic understanding of tumor evolution that can be leveraged to study targeted immunotherapeutic strategies.

Comparative morphology of tumour microenvironment in claudin-low and claudin-high breast cancers

BACKGROUND

Claudin-low breast cancers (BCs) exhibit more aggressive behaviour compared to claudin-high types. Claudin-low BCs are often characterized by features such as a higher grade, enrichment of stemness characteristics, and a propensity for metastasis. Tumour microenvironment (TME) defined as the intricate network of surrounding cells, blood vessels, and extracellular matrix components influences the behaviour of cancer cells within the breast tissue. Understanding the TME is crucial for comprehending the aggressive characteristics of claudin-low BCs.

METHODS

In this study, we have studied the morphology of immune and non-immune TME using Haematoxylin and eosin (H&E)-stained slides of 15 claudin-low and 12 claudin-high tissue samples of BC.

RESULTS

TME of claudin-low BCs was observed to have a significantly higher frequency of retraction clefts (66.6 %; n = 10/15), immature desmoplastic response (40 %; n = 6/15), higher stromal cellularity (60 %; n = 9/15); and fibroblastic proliferation (53.3 %; n = 8/15) with a low prevalence of elastosis (66.6 %; n = 10/15). The immune microenvironment revealed a higher frequency of total (80 %; n = 12/15) as well as stromal (86.67 %; n = 13/15) and intra-tumoural TILs (60 %; n = 9/15) in them.

CONCLUSION

The above morphology-based study revealed that claudin-low tumours have unique immune and non-immune TME as compared to claudin-high tumours. Future studies exploring the molecular correlates of each of the above morphological features can help in identifying novel therapeutic targets for the treatment of claudin-low BCs.

Decoding the Role of Insulin-like Growth Factor 1 and Its Isoforms in Breast Cancer

Insulin-like Growth Factor-1 (IGF-1) is a crucial mitogenic factor with important functions in the mammary gland, mainly through its interaction with the IGF-1 receptor (IGF-1R). This interaction activates a complex signaling network that promotes cell proliferation, epithelial to mesenchymal transition (EMT) and inhibits apoptosis. Despite extensive research, the precise molecular pathways and intracellular mechanisms activated by IGF-1, in cancer, remain poorly understood. Recent evidence highlights the essential roles of IGF-1 and its isoforms in breast cancer (BC) development, progression, and metastasis. The peptides that define the IGF-1 isoforms-IGF-1Ea, IGF-1Eb, and IGF-1Ec-act as key points of convergence for various signaling pathways that influence the growth, metastasis and survival of BC cells. The aim of this review is to provide a detailed exami-nation of the role of the mature IGF-1 and its isoforms in BC biology and their potential use as possible therapeutical targets.

The next frontier in immunotherapy: potential and challenges of CAR-macrophages

Chimeric antigen receptor macrophage (CAR-MΦ) represents a significant advancement in immunotherapy, especially for treating solid tumors where traditional CAR-T therapies face limitations. CAR-MΦ offers a promising approach to target and eradicate tumor cells by utilizing macrophages' phagocytic and antigen-presenting abilities. However, challenges such as the complex tumor microenvironment (TME), variability in antigen expression, and immune suppression limit their efficacy. This review addresses these issues, exploring mechanisms of CAR-MΦ action, optimal construct designs, and interactions within the TME. It also delves into the ex vivo manufacturing challenges of CAR-MΦ, discussing autologous and allogeneic sources and the importance of stringent quality control. The potential synergies of integrating CAR-MΦ with existing cancer therapies like checkpoint inhibitors and conventional chemotherapeutics are examined to highlight possible enhanced treatment outcomes. Furthermore, regulatory pathways for CAR-MΦ therapies are scrutinized alongside established protocols for CAR-T cells, identifying unique considerations essential for clinical trials and market approval. Proposed safety monitoring frameworks aim to manage potential adverse events, such as cytokine release syndrome, crucial for patient safety. Consolidating current research and clinical insights, this review seeks to refine CAR-MΦ therapeutic applications, overcome barriers, and suggest future research directions to transition CAR-MΦ therapies from experimental platforms to standard cancer care options.

New paradigms to break barriers in early cancer detection for improved prognosis and treatment outcomes

The uncontrolled growth and spread of cancerous cells beyond their usual boundaries into surrounding tissues characterizes cancer. In developed countries, cancer is the leading cause of death, while in underdeveloped nations, it ranks second. Using existing cancer diagnostic tools has increased early detection rates, which is crucial for effective cancer treatment. In recent decades, there has been significant progress in cancer-specific survival rates owing to advances in cancer detection and treatment. The ability to accurately identify precursor lesions is a crucial aspect of effective cancer screening programs, as it enables early treatment initiation, leading to lower long-term incidence of invasive cancer and improved overall prognosis. However, these diagnostic methods have limitations, such as high costs and technical challenges, which can make accurate diagnosis of certain deep-seated tumors difficult. To achieve accurate cancer diagnosis and prognosis, it is essential to continue developing cutting-edge technologies in molecular biology and cancer imaging.

Integrating single-cell transcriptomics and machine learning to predict breast cancer prognosis: A study based on natural killer cell-related genes

Breast cancer (BC) is the most commonly diagnosed cancer in women globally. Natural killer (NK) cells play a vital role in tumour immunosurveillance. This study aimed to establish a prognostic model using NK cell-related genes (NKRGs) by integrating single-cell transcriptomic data with machine learning. We identified 44 significantly expressed NKRGs involved in cytokine and T cell-related functions. Using 101 machine learning algorithms, the Lasso + RSF model showed the highest predictive accuracy with nine key NKRGs. We explored cell-to-cell communication using CellChat, assessed immune-related pathways and tumour microenvironment with gene set variation analysis and ssGSEA, and observed immune components by HE staining. Additionally, drug activity predictions identified potential therapies, and gene expression validation through immunohistochemistry and RNA-seq confirmed the clinical applicability of NKRGs. The nomogram showed high concordance between predicted and actual survival, linking higher tumour purity and risk scores to a reduced immune score. This NKRG-based model offers a novel approach for risk assessment and personalized treatment in BC, enhancing the potential of precision medicine.

Intratumoral delivery of immunotherapy to treat breast cancer: current development in clinical and preclinical studies

Breast cancer poses one of the largest threats to women's health. Treatment continues to improve for all the subtypes of breast cancer, but some subtypes, such as triple negative breast cancer, still present a significant treatment challenge. Additionally, metastasis and local recurrence are two prevalent problems in breast cancer treatment. A newer type of therapy, immunotherapy, may offer alternatives to traditional treatments for difficult-to-treat subtypes. Immunotherapy engages the host's immune system to eradicate disease, with the potential to induce long-lasting, durable responses. However, systemic immunotherapy is only approved in a limited number of indications, and it benefits only a minority of patients. Furthermore, immune related toxicities following systemic administration of potent immunomodulators limit dosing and, consequently, efficacy. To address these safety considerations and improve treatment efficacy, interest in local delivery at the site of the tumor has increased. Numerous intratumorally delivered immunotherapeutics have been and are being explored clinically and preclinically, including monoclonal antibodies, cellular therapies, viruses, nucleic acids, cytokines, innate immune agonists, and bacteria. This review summarizes the current and past intratumoral immunotherapy clinical landscape in breast cancer as well as current progress that has been made in preclinical studies, with a focus on delivery parameters and considerations.

Exploring the Immunological Profile in Breast Cancer: Recent Advances in Diagnosis and Prognosis through Circulating Tumor Cells

This review offers a comprehensive exploration of the intricate immunological landscape of breast cancer (BC), focusing on recent advances in diagnosis and prognosis through the analysis of circulating tumor cells (CTCs). Positioned within the broader context of BC research, it underscores the pivotal role of the immune system in shaping the disease's progression. The primary objective of this investigation is to synthesize current knowledge on the immunological aspects of BC, with a particular emphasis on the diagnostic and prognostic potential offered by CTCs. This review adopts a thorough examination of the relevant literature, incorporating recent breakthroughs in the field. The methodology section succinctly outlines the approach, with a specific focus on CTC analysis and its implications for BC diagnosis and prognosis. Through this review, insights into the dynamic interplay between the immune system and BC are highlighted, with a specific emphasis on the role of CTCs in advancing diagnostic methodologies and refining prognostic assessments. Furthermore, this review presents objective and substantiated results, contributing to a deeper understanding of the immunological complexity in BC. In conclusion, this investigation underscores the significance of exploring the immunological profile of BC patients, providing valuable insights into novel advances in diagnosis and prognosis through the utilization of CTCs. The objective presentation of findings emphasizes the crucial role of the immune system in BC dynamics, thereby opening avenues for enhanced clinical management strategies.

Identification of a Group of Therapeutic Targets and Prognostic Biomarker for Triple Negative Breast Cancer

INTRODUCTION

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Mining differentially expressed genes of TNBC is helpful to explore new therapeutic targets. This study aimed to investigate diagnostic biomarker genes in TNBC compared to normal tissue. Additionally, we explored the functions and prognostic value of these key genes as well as potential targeted drugs that could affect these genes.

METHODS

Differential gene expression analysis was conducted using the R software with data from the Gene Expression Omnibus (GEO) database. Then, the identified differentially expressed genes (DEGs) were used to construct a protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The mRNA expression levels of key genes were analyzed using the UALCAN database with data from The Cancer Genome Atlas (TCGA). Enrichment and survival analyses were performed using R software. In addition, potential compounds showing sensitivity to key genes were identified by gene set cancer analysis (GSCA).

RESULTS

Compared with normal tissues, a total of 203 DEGs were upregulated in TNBC. These DEGs participated in various biological processes including nuclear division, microtubule binding, cell cycle, and the p53 signaling pathway. Through the PPI network analysis, ten key genes were identified, among which four genes showed significant correlation with poor progression-free interval (PFI) in patients with TNBC. Moreover, the four survival-related genes were found to act as sensitive therapeutic targets.

CONCLUSION

The identified four key genes were considered new biomarkers for diagnosis and prognosis and also potential therapeutic targets for TNBC.

Genomic Features of Homologous Recombination Deficiency in Breast Cancer: Impact on Testing and Immunotherapy

Genomic instability is one of the well-established hallmarks of cancer. The homologous recombination repair (HRR) pathway plays a critical role in correcting the double-stranded breaks (DSB) due to DNA damage in human cells. Traditionally, the BRCA1/2 genes in the HRR pathway have been tested for their association with breast cancer. However, defects in the HRR pathway (HRD, also termed 'BRCAness'), which has up to 50 genes, have been shown to be involved in tumorigenesis and treatment susceptibility to poly-ADP ribose polymerase inhibitors (PARPis), platinum-based chemotherapy, and immune checkpoint inhibitors (ICIs). A reliable consensus on HRD scores is yet to be established. Emerging evidence suggests that only a subset of breast cancer patients benefit from ICI-based immunotherapy. Currently, albeit with limitations, the expression of programmed death-ligand 1 (PDL1) and tumor mutational burden (TMB) are utilized as biomarkers to predict the favorable outcomes of ICI therapy in breast cancer patients. Preclinical studies demonstrate an interplay between the HRR pathway and PDL1 expression. In this review, we outline the current understanding of the role of HRD in genomic instability leading to breast tumorigenesis and delineate outcomes from various clinical trials. Furthermore, we discuss potential strategies for combining HRD-targeted therapy with immunotherapy to achieve the best healthcare outcomes in breast cancer patients.

The Tumor Microenvironment and Immune Response in Breast Cancer

The complex interactions between cancer cells and their surrounding microenvironment are fundamental in determining tumor progression, response to therapy, and, ultimately, patient prognosis [...].