‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’

Multi-omic profiling in breast cancer: utility for advancing diagnostics and clinical care

INTRODUCTION

Breast cancer remains a major global health challenge. While advances in precision oncology have contributed to improvements in patient outcomes and provided a deeper understanding of the biological mechanisms that drive the disease, historically, research and patients' allocation to treatment have heavily relied on single-omic approaches, analyzing individual molecular dimensions such as genomics, transcriptomics, or proteomics. While these have provided deep insights into breast cancer biology, they often fail to offer a complete understanding of the disease's complex molecular landscape.

AREAS COVERED

In this review, the authors explore the recent advancements in multi-omic research in the realm of breast cancer and use clinical data to show how multi-omic integration can offer a more holistic understanding of the molecular alterations and their functional consequences underlying breast cancer.

EXPERT OPINION

The overall developments in multi-omic research and AI are expected to complement precision diagnostics through potentially refining prognostic models, and treatment selection. Overcoming challenges such as cost, data complexity, and lack of standardization is crucial for unlocking the full potential of multi-omics and AI in breast cancer patient care to enable the advancement of personalized treatments and improve patient outcomes.

Radiogenomic Landscape of Metastatic Endocrine-Positive Breast Cancer Resistant to Aromatase Inhibitors

Breast cancer poses a significant global health challenge and includes various subtypes, such as endocrine-positive, HER2-positive, and triple-negative. Endocrine-positive breast cancer, characterized by estrogen and progesterone receptors, is commonly treated with aromatase inhibitors. However, resistance to these inhibitors can hinder patient outcomes due to genetic and epigenetic alterations, mutations in the estrogen receptor 1 gene, and changes in signaling pathways. Radiogenomics combines imaging techniques like MRI and CT scans with genomic profiling methods to identify radiographic biomarkers associated with resistance. This approach enhances our understanding of resistance mechanisms and metastasis patterns, linking them to specific genomic profiles and common metastasis sites like the bone and brain. By integrating radiogenomic data, personalized treatment strategies can be developed, improving predictive and prognostic capabilities. Advancements in imaging and genomic technologies offer promising avenues for enhancing radiogenomic research. A thorough understanding of resistance mechanisms is crucial for developing effective treatment strategies, making radiogenomics a valuable integrative approach in personalized medicine that aims to improve clinical outcomes for patients with metastatic endocrine-positive breast cancer.

Genetic advancements in breast cancer treatment: a review

Breast cancer (BC) remains a leading cause of cancer-related deaths among women globally, highlighting the urgent need for more effective and targeted therapies. Traditional treatments, including surgery, chemotherapy, and radiation, face limitations such as drug resistance, metastasis, and severe side effects. Recent advancements in gene therapy, particularly CRISPR/Cas9 technology and Oncolytic Virotherapy (OVT), are transforming the BC treatment landscape. CRISPR/Cas9 enables precise gene editing to correct mutations in oncogenes like HER2 and MYC, directly addressing tumor growth and immune evasion. Simultaneously, OVT leverages genetically engineered viruses to selectively destroy cancer cells and stimulate robust antitumor immune responses. Despite their potential, gene therapies face challenges, including off-target effects, delivery issues, and ethical concerns. Innovations in delivery systems, combination strategies, and integrating gene therapy with existing treatments offer promising solutions to overcome these barriers. Personalized medicine, guided by genomic profiling, further enhances treatment precision by identifying patient-specific mutations, such as BRCA1 and BRCA2, allowing for more tailored and effective interventions. As research progresses, the constructive interaction between gene therapy, immunotherapy, and traditional approaches is paving the way for groundbreaking advancements in BC care. Continued collaboration between researchers and clinicians is essential to translate these innovations into clinical practice, ultimately improving BC patients' survival rates and quality of life.

Role of PD-1 in modulating IFN-γ-CXCL9/10-CXCR3 signaling in breast cancer

Breast cancer represents a significant health burden globally, necessitating ongoing advancements in treatment strategies for improved patient outcomes. Immunotherapy, particularly targeting immune checkpoints like programmed death-1 (PD-1), has emerged as a promising approach in cancer therapy. This study focuses on elucidating the role of PD-1 in modulating the IFN-γ-CXCL9/10-CXCR3 signaling axis within the breast cancer microenvironment. By investigating the synergistic effects of PD-1 inhibitors in combination with Inetetamab, our research aims to uncover novel therapeutic targets for enhancing immunotherapy efficacy in breast cancer. Through comprehensive experimental analysis, we seek to deepen our understanding of the intricate molecular mechanisms underlying immune regulation in breast cancer, thereby paving the way for more effective and sustainable treatment strategies. Ultimately, our study endeavors to establish a robust theoretical framework that can guide the development of innovative clinical interventions, aiming for improved outcomes in breast cancer patients.

Precision medicine in breast cancer (Review)

Precision medicine in breast cancer is a revolutionary approach that customizes diagnosis and treatment based on individual and tumor characteristics, departing from the traditional one-size-fits-all approach. Breast cancer is diverse, with various subtypes driven by distinct genetic mutations. Understanding this diversity is crucial for tailored treatment strategies that target specific vulnerabilities in each tumor. Genetic testing, particularly for mutations in breast cancer gene (BRCA) DNA repair-associated genes, helps assess hereditary risks and influences treatment decisions. Molecular subtyping guides personalized treatments, such as hormonal therapies for receptor-positive tumors and human epidermal growth factor receptor 2 (HER2)-targeted treatments. Targeted therapies, including those for HER2-positive and hormone receptor-positive breast cancers, offer more effective and precise interventions. Immunotherapy, especially checkpoint inhibitors, shows promise, particularly in certain subtypes such as triple-negative breast cancer, with ongoing research aiming to broaden its effectiveness. Integration of big data and artificial intelligence enhances personalized treatment strategies, while liquid biopsies provide real-time insights into tumor dynamics, aiding in treatment monitoring and modification. Challenges persist, including accessibility and tumor complexity, but emerging technologies and precision prevention offer hope for improved outcomes. Ultimately, precision medicine aims to optimize treatment efficacy, minimize adverse effects and enhance the quality of life for patients with breast cancer.

Implications of Agile Values in Software Engineering for Agility in Breast Cancer Treatment: Protocol for a Comparative Study

BACKGROUND

Breast cancer treatment has been described as a dynamic and patient-centered approach that emphasizes adaptability and flexibility throughout the treatment process. Breast cancer is complex, with varying subtypes and stages, making it important to tailor treatment plans to each patient's unique circumstances. Breast cancer treatment delivery relies on a multidisciplinary team of health care professionals who collaborate to provide personalized care and quick adaptation to changing conditions to optimize outcomes while minimizing side effects and maintaining the patient's quality of life. However, agility in breast cancer treatment has not been defined according to common agile values and described in language comprehensible to breast cancer professionals. In the rapidly evolving landscape of breast cancer treatment, the incorporation of agile values from software engineering promises to enhance patient care.

OBJECTIVE

Our objective is to propose agile values for breast cancer treatment adopted and adapted from software engineering. We also aim to validate how these values conform to the concept of agility in the breast cancer context through referencing past work.

METHODS

We applied a structured research methodology to identify and validate 4 agile values for breast cancer treatment. In the elicitation phase, through 2 interviews, we identified 4 agile values and described them in language that resonates with breast cancer treatment professionals. The values were then validated by a domain expert and discussed in the context of supporting work from the literature. Final validation entailed a domain expert conducting a walkthrough of the 4 identified agile values to adjust them as per the reported literature.

RESULTS

Four agile values were identified for breast cancer treatment, and among them, we validated 3 that conformed to the concept of agility. The fourth value, documentation and the quality of documentation, is vital for breast cancer treatment planning and management. This does not conform to agility. However, its nonagility is vital for the agility of the other values. None of the identified agile values were validated as partially conforming to the concept of agility.

CONCLUSIONS

This work makes a novel contribution to knowledge in identifying the first set of agile values in breast cancer treatment through multidisciplinary research. Three of these values were evaluated as conforming to the concept of agility, and although 1 value did not meet the concept of agility, it enhanced the agility of the other values. It is anticipated that these 4 agile values can drive oncology practice, strategies, policies, protocols, and procedures to enhance delivery of care. Moreover, the identified values contribute to identifying quality assurance and control practices to assess the concept of agility in oncology practice and breast cancer treatment and adjust corresponding actions. We conclude that breast cancer treatment agile values are not limited to 4.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/53124.

Breast cancer vaccines; A comprehensive and updated review

According to the International Agency for Research on Cancer, breast cancer is more common than lung cancer globally. By 2040, mortality from breast cancer will rise by 50% and 40%, respectively. Despite advances in chemotherapy, endocrine therapy, and HER2-targeted therapy, breast cancer metastases and recurrences remain challenging to treat. Cancer vaccines are an effective treatment option because they stimulate a long-lasting immune response that will eliminate tumor cells. In studies on the breast cancer vaccine, no appreciable advantages were discovered. A recent study claims that immune checkpoint inhibitors or anti-HER2 monoclonal antibodies may be used in vaccinations. This vaccination strengthens the immune system to fight off breast cancer cells. Clinical trials have been conducted on DNA, dendritic cells, and peptide-based breast cancer vaccines. Studies on the breast cancer vaccine have employed subcutaneous, intramuscular, and intradermal injections. Clinical studies have shown that these efforts have not been successful. Several factors might have slowed the development of a breast cancer vaccine. The complexity of the immune system makes it challenging to create cancer vaccines. Given the heterogeneity of breast cancer, there may be a need for different vaccination strategies. Despite these obstacles, research into breast cancer vaccines continues. Effective methods for creating vaccines include immune checkpoint inhibition and anti-HER2 monoclonal antibodies. Research is also being done on specialized tumor vaccinations.

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Molecular mechanisms of multi-omic regulation in breast cancer

Breast cancer is a complex disease that is influenced by the concurrent influence of multiple genetic and environmental factors. Recent advances in genomics and other high throughput biomolecular techniques (-omics) have provided numerous insights into the molecular mechanisms underlying breast cancer development and progression. A number of these mechanisms involve multiple layers of regulation. In this review, we summarize the current knowledge on the role of multiple omics in the regulation of breast cancer, including the effects of DNA methylation, non-coding RNA, and other epigenomic changes. We comment on how integrating such diverse mechanisms is envisioned as key to a more comprehensive understanding of breast carcinogenesis and cancer biology with relevance to prognostics, diagnostics and therapeutics. We also discuss the potential clinical implications of these findings and highlight areas for future research. Overall, our understanding of the molecular mechanisms of multi-omic regulation in breast cancer is rapidly increasing and has the potential to inform the development of novel therapeutic approaches for this disease.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Morphological Dependence of Breast Cancer Cell Responses to Doxorubicin on Micropatterned Surfaces

Cell morphology has been widely investigated for its influence on the functions of normal cells. However, the influence of cell morphology on cancer cell resistance to anti-cancer drugs remains unclear. In this study, micropatterned surfaces were prepared and used to control the spreading area and elongation of human breast cancer cell line. The influences of cell adhesion area and elongation on resistance to doxorubicin were investigated. The percentage of apoptotic breast cancer cells decreased with cell spreading area, while did not change with cell elongation. Large breast cancer cells had higher resistance to doxorubicin, better assembled actin filaments, higher DNA synthesis activity and higher expression of P-glycoprotein than small breast cancer cells. The results suggested that the morphology of breast cancer cells could affect their resistance to doxorubicin. The influence was correlated with cytoskeletal organization, DNA synthesis activity and P-glycoprotein expression.