Targeted therapies in breast cancer: New challenges to fight against resistance

Deep Radiogenomics Sequencing for Breast Tumor Gene-Phenotype Decoding Using Dynamic Contrast Magnetic Resonance Imaging

PURPOSE

We aim to perform radiogenomic profiling of breast cancer tumors using dynamic contrast magnetic resonance imaging (MRI) for the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) genes.

METHODS

The dataset used in the current study consists of imaging data of 922 biopsy-confirmed invasive breast cancer patients with ER, PR, and HER2 gene mutation status. Breast MR images, including a T1-weighted pre-contrast sequence and three post-contrast sequences, were enrolled for analysis. All images were corrected using N4 bias correction algorithms. Based on all images and tumor masks, a bounding box of 128 × 128 × 68 was chosen to include all tumor regions. All networks were implemented in 3D fashion with input sizes of 128 × 128 × 68, and four images were input to each network for multi-channel analysis. Data were randomly split into train/validation (80%) and test set (20%) with stratification in class (patient-wise), and all metrics were reported in 20% of the untouched test dataset.

RESULTS

For ER prediction, SEResNet50 achieved an AUC mean of 0.695 (CI95%: 0.610-0.775), a sensitivity of 0.564, and a specificity of 0.787. For PR prediction, ResNet34 achieved an AUC mean of 0.658 (95% CI: 0.573-0.741), a sensitivity of 0.593, and a specificity of 0.734. For HER2 prediction, SEResNext101 achieved an AUC mean of 0.698 (95% CI: 0.560-0.822), a sensitivity of 0.750, and a specificity of 0.625.

CONCLUSION

The current study demonstrated the feasibility of imaging gene-phenotype decoding in breast tumors using MR images and deep learning algorithms with moderate performance.

Self-assembled Lipid Nanoparticles for Killing Triple Negative Breast Cancer Cells

Triple negative breast cancers (TNBCs) lacking estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) on their cell surfaces are highly aggressive, difficult-to-treat and often relapse. Herein, we report on the self-assembled lipid nanoparticles (LNPs) of two new pegylated lipopeptides for killing TNBCs (MDA-MB-231). The pegylated lipopeptides were synthesized by conjugating an n-hexadecyl hydrophobic tail to one end of a (PEG)27 unit the other distal end of which was covalently grafted with two previously reported tumor targeting RGDK- and CGKRK- peptides. The SEM images of the self-assembled LNPs formed upon dissolution of the pegylated lipopeptides in aqueous medium revealed formation of spherical aggregates. The degree of cellular uptake for the self-assembled LNPs formed by the pegylated CGKRK-lipopeptide were found to be significantly higher than that for the self-assembled LNPs formed by the pegylated RGDK-lipopeptide in MCF-7, MDA-MB-231, HEK-293 and HFF cells. Notably, about 60 % TNBCs (MDA-MB-231 cells) were killed upon treatment with commercially available potent JAK2 inhibitor (WP 1066) loaded LNPs of the pegylated RGDK-lipopeptide. Contrastingly, the same treatment killed only about 20 % non-cancerous HEK-293 cells. The self-assembled pegylated LNPs described herein open the door for undertaking preclinical studies in animal models for TNBCs.

Unraveling non-coding RNAs in breast cancer: mechanistic insights and therapeutic potential

Breast cancer remains a leading global health challenge requiring innovative, therapeutic strategies to improve patient outcomes. This review explores the pivotal roles of non-coding RNAs (ncRNAs), including long non-coding RNA, micro RNA, and circular RNA, in breast cancer biology. We highlight how these molecules regulate critical signaling pathways, influence tumor microenvironments, and contribute to treatment resistance. Our findings underscore the potential of ncRNAs as biomarkers for early diagnosis and as treatment targets for personalized treatment strategies. To pave the way for innovative cancer management approaches, we investigate the complex interactions of ncRNAs and their impact on tumor progression. This comprehensive review enhances our understanding of breast cancer biology while emphasizing the translational significance of ncRNA research in developing effective treatment strategies. Additional research and clinical studies are required to confirm the diagnostic and medicinal value of ncRNAs in breast cancer. Investigating the complex networks of ncRNA interactions and their links to other biological pathways can lead to the discovery of new treatment targets. Furthermore, leveraging advanced technologies, such as machine learning and multi-omics methods, will be critical in improving our understanding of ncRNAs biomarkers and translating these insights into impactful clinical applications.

Development of bioengineered 3D patient derived breast cancer organoid model focusing dynamic fibroblast-stem cell reciprocity

Three-dimensional (3D) models, such as tumor spheroids and organoids, are increasingly developed by integrating tissue engineering, regenerative medicine, and personalized therapy strategies. These advanced 3Din-vitromodels are not merely endpoint-driven but also offer the flexibility to be customized or modulated according to specific disease parameters. Unlike traditional 2D monolayer cultures, which inadequately capture the complexities of solid tumors, 3D co-culture systems provide a more accurate representation of the tumor microenvironment. This includes critical interactions with mesenchymal stem/stromal cells (MSCs) and induced pluripotent stem cells (iPSCs), which significantly modulate cancer cell behavior and therapeutic responses. Most of the findings from the co-culture of Michigan Cancer Foundation-7 breast cancer cells and MSC showed the formation of monolayers. Although changes in the plasticity of MSCs and iPSCs caused by other cells and extracellular matrix (ECM) have been extensively researched, the effect of MSCs on cancer stem cell (CSC) aggressiveness is still controversial and contradictory among different research communities. Some researchers have argued that CSCs proliferate more, while others have proposed that cancer spread occurs through dormancy. This highlights the need for further investigation into how these interactions shape cancer aggressiveness. The objective of this review is to explore changes in cancer cell behavior within a 3D microenvironment enriched with MSCs, iPSCs, and ECM components. By describing various MSC and iPSC-derived 3D breast cancer models that replicate tumor biology, we aim to elucidate potential therapeutic targets for breast cancer. A particular focus of this review is the Transwell system, which facilitates understanding how MSCs and iPSCs affect critical processes such as migration, invasion, and angiogenesis. The gradient formed between the two chambers is based on diffusion, as seen in the human body. Once optimized, this Transwell model can serve as a high-throughput screening platform for evaluating various anticancer agents. In the future, primary cell-based and patient-derived 3D organoid models hold promise for advancing personalized medicine and accelerating drug development processes.

Impact of prolactin treatment on enhancing the cellular responses of MCF7 breast cancer cells to tamoxifen treatment

Breast cancer remains one of the most challenging diseases to treat due to its heterogeneity, propensity to recur, capacity to spread to distant vital organs, and, ultimately, patient death. Estrogen receptor-positive illness comprises the most common breast cancer subtype. Preclinical progress is hampered by the scarcity of medication-naïve estrogen receptor-positive tumour models that recapitulate metastatic development and treatment resistance. It is becoming increasingly clear that loss of differentiation and increased cellular stemness and plasticity are important causes of cancer evolution, heterogeneity, recurrence, metastasis, and treatment failure. Therefore, it has been suggested that reprogramming cancer cell differentiation could offer an effective method of reversing cancer through terminal differentiation and maturation. In this context, the hormone prolactin is well recognized for its pivotal involvement in the development of the mammary glands lobuloalveolar tissue and the terminal differentiation that drives the production of the milk protein gene and lactation. Additionally, numerous studies have examined the engagement of prolactin in breast cancer as a differentiation player that resulted in the ablation of tumour growth and progression. Here, we showed that a pre-treatment of the estrogen-positive breast cancer cell line with prolactin led to a considerable improvement in the sensitivity of this cancer cell to Tamoxifen endocrine therapy. We also showed a favourable prognostic value of prolactin receptors/estrogen receptors 1 (or alpha) co-expression on breast cancer patients outcomes, and this co-expression is highly correlated with the well-differentiated breast tumour type. Our results revealed a fruitful aspect of the effects of prolactin in improving the responses of breast cancer cells to conventional endocrine therapy. Moreover, these findings further validated the ability of prolactin as a persuader of a more differentiated and less aggressive breast cancer phenotype. Hence, it suggested a potential implication of prolactin as a therapeutic candidate.

Failure to progress: breast and prostate cancer cell lines in developing targeted therapies

Developing anticancer drugs from preclinical to clinical takes approximately a decade in a cutting-edge biomedical lab and still 97% of most fail at clinical trials. Cell line usage is critical in expediting the advancement of anticancer therapies. Yet developing appropriate cell lines has been challenging and overcoming these obstacles whilst implementing a systematic approach of utilizing 3D models that recapitulate the tumour microenvironment is prudent. Using a robust and continuous supply of cell lines representing all ethnic groups from all locales is necessary to capture the evolving tumour landscape in culture. Next, the conversion of these models to systems on a chip that can by way of high throughput cytotoxic assays identify drug leads for clinical trials should fast-track drug development while markedly improving success rates. In this review, we describe the challenges that have hindered the progression of cell line models over seven decades and methods to overcome this. We outline the gaps in breast and prostate cancer cell line pathology and racial representation alongside their involvement in relevant drug development.

The EORTC QLQ breast modules and the FACT-B for assessing quality of life in breast cancer patients - an updated literature review

PURPOSE OF REVIEW

Two commonly used quality of life questionnaires in breast cancer are EORTC QLQ-BR23, the FACT-B, and the extended FACT-B + 4. More recently, the EORTC EORTC QLQ-BR42 was developed. This systematic review compares the various versions of the EORTC QLQ and FACT tools for breast cancer in terms of their content, validity, and psychometric properties.

RECENT FINDINGS

Thirty-six studies met the inclusion criteria. All questionnaires have been proven to be valid, reliable and responsive. The provisional EORTC QLQ-BR45 transitioned to the EORTC QLQ-BR42 in Phase IV of its development, which encompasses the side effects associated with the latest breast cancer treatments. Both the EORTC and FACT measures assess physical and mental dimensions of quality of life, with the EORTC measure placing relatively more emphasis on physical content and FACT placing relatively more emphasis on mental (social and emotional) content. The four additional items in the FACT-B + 4 were developed to address arm lymphoedema following axillary surgery.

SUMMARY

The development and uptake of quality of life tools are essential in the evaluation of breast cancer treatments. The EORTC QLQ-BR42 and FACT-B are both valid, reliable, and responsive QoL questionnaires.

Celecoxib inhibits NLRP1 inflammasome pathway in MDA-MB-231 Cells

NLRP1 is predominantly overexpressed in breast cancer tissue, and the evaluated activation of NLRP1 inflammasome is associated with tumor growth, angiogenesis, and metastasis. Therefore, targeting NLRP1 activation could be a crucial strategy in anticancer therapy. In this study, we investigated the hypothesis that NLRP1 pathway may contribute to the cytotoxic effects of celecoxib and nimesulide in MDA-MB-231 cells. First of all, IC50 values and inhibitory effects on the colony-forming ability of drugs were evaluated in cells. Then, the alterations in the expression levels of NLRP1 inflammasome components induced by drugs were investigated. Subsequently, the release of inflammatory cytokine IL-1β and the activity of caspase-1 in drug-treated cells were measured. According to our results, celecoxib and nimesulide selectively inhibited the viability of MDA-MB-231 cells. These drugs remarkably inhibited the colony-forming ability of cells. The expression levels of NLRP1 inflammasome components decreased in celecoxib-treated cells, accompanied by decreased caspase-1 activity and IL-1β release. In contrast, nimesulide treatment led to the upregulation of the related protein expressions with unchanged caspase-1 activity and increased IL-1β secretion. Our results indicated that the NLRP1 inflammasome pathway might contribute to the antiproliferative effects of celecoxib in MDA-MB-231 cells but is not a crucial mechanism for nimesulide.

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.

Targeting overexpressed surface proteins: A new strategy to manage the recalcitrant triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous cancer that lacks all three molecular markers, Estrogen, Progesterone, and Human Epidermal Growth Factor Receptor 2 (HER2). This unique characteristic of TNBC makes it more resistant to hormonal therapy; hence, chemotherapy and surgery are preferred. Active targeting with nanoparticles is more effective in managing TNBC than a passive approach. The surface of TNBC cells overexpresses several cell-specific proteins, which can be explored for diagnostic and therapeutic purposes. Immunohistochemical analysis has revealed that TNBC cells overexpress αVβ3 integrin, Intercellular Adhesion Molecule 1 (ICAM-1), Glucose Transporter 5 (GLUT5), Transmembrane Glycoprotein Mucin 1 (MUC-1), and Epidermal Growth Factor Receptor (EGFR). These surface proteins can be targeted using ligands, such as aptamers, antibodies, and sugar molecules. Targeting the surface proteins of TNBC with ligands helps harmonize treatment and improve patient compliance. In this review, we discuss the proteins expressed, which are limited to αVβ3 integrin proteins, ICAM-1, GLUT-5, MUC1, and EGFR, on the surface of TNBC, the challenges associated with the preclinical setup of breast cancer for targeted nanoformulations, internalization techniques and their challenges, suggestions to overcome the limitations of successful translation of nanoparticles, and the possibility of ligand-conjugated nanoparticles targeting these surface receptors for a better therapeutic outcome.

MicroRNA-21 (miR-21) in breast cancer: From apoptosis dysregulation to therapeutic opportunities

Breast cancer, a pervasive and complex disease, continues to pose significant challenges in the field of oncology. Its heterogeneous nature and diverse molecular profiles necessitate a nuanced understanding of the underlying mechanisms driving tumorigenesis and progression. MicroRNA-21 (miR-21) has emerged as a crucial player in breast cancer development and progression by modulating apoptosis, a programmed cell death mechanism that eliminates aberrant cells. MiR-21 overexpression is a hallmark of breast cancer, and it is associated with poor prognosis and resistance to conventional therapies. This miRNA exerts its oncogenic effects by targeting various pro-apoptotic genes, including Fas ligand (FasL), programmed cell death protein 4 (PDCD4), and phosphatase and tensin homolog (PTEN). By suppressing these genes, miR-21 promotes breast cancer cell survival, proliferation, invasion, and metastasis. The identification of miR-21 as a critical regulator of apoptosis in breast cancer has opened new avenues for therapeutic intervention. This review investigates the intricate mechanisms through which miR-21 influences apoptosis, offering insights into the molecular pathways and signaling cascades involved. The dysregulation of apoptosis is a hallmark of cancer, and understanding the role of miR-21 in this context holds immense therapeutic potential. Additionally, the review highlights the clinical significance of miR-21 as a diagnostic and prognostic biomarker in breast cancer, underscoring its potential as a therapeutic target.

A molecular switch from tumor suppressor to oncogene in ER+ve breast cancer: Role of androgen receptor, JAK-STAT, and lineage plasticity

Cancers develop resistance to inhibitors of oncogenes mainly due to target-centric mechanisms such as mutations and splicing. While inhibitors or antagonists force targets to unnatural conformation contributing to protein instability and resistance, activating tumor suppressors may maintain the protein in an agonistic conformation to elicit sustainable growth inhibition. Due to the lack of tumor suppressor agonists, this hypothesis and the mechanisms underlying resistance are not understood. In estrogen receptor (ER)-positive breast cancer (BC), androgen receptor (AR) is a druggable tumor suppressor offering a promising avenue for this investigation. Spatial genomics suggests that the molecular portrait of AR-expressing BC cells in tumor microenvironment corresponds to better overall patient survival, clinically confirming AR's role as a tumor suppressor. Ligand activation of AR in ER-positive BC xenografts reprograms cistromes, inhibits oncogenic pathways, and promotes cellular elasticity toward a more differentiated state. Sustained AR activation results in cistrome rearrangement toward transcription factor PROP paired-like homeobox 1, transformation of AR into oncogene, and activation of the Janus kinase/signal transducer (JAK/STAT) pathway, all culminating in lineage plasticity to an aggressive resistant subtype. While the molecular profile of AR agonist-sensitive tumors corresponds to better patient survival, the profile represented in the resistant phenotype corresponds to shorter survival. Inhibition of activated oncogenes in resistant tumors reduces growth and resensitizes them to AR agonists. These findings indicate that persistent activation of a context-dependent tumor suppressor may lead to resistance through lineage plasticity-driven tumor metamorphosis. Our work provides a framework to explore the above phenomenon across multiple cancer types and underscores the importance of factoring sensitization of tumor suppressor targets while developing agonist-like drugs.

The Proapoptotic Action of Pyrrolidinedione-Thiazolidinone Hybrids towards Human Breast Carcinoma Cells Does Not Depend on Their Genotype

The development of new, effective agents for the treatment of breast cancer remains a high-priority task in oncology. A strategy of treatment for this pathology depends significantly on the genotype and phenotype of human breast cancer cells. We aimed to investigate the antitumor activity of new pyrrolidinedione-thiazolidinone hybrid molecules Les-6287, Les-6294, and Les-6328 towards different types of human breast cancer cells of MDA-MB-231, MCF-7, T-47D, and HCC1954 lines and murine breast cancer 4T1 cells by using the MTT, clonogenic and [3H]-Thymidine incorporation assays, flow cytometry, ELISA, and qPCR. The studied hybrids possessed toxicity towards the mentioned tumor cells, with the IC50 ranging from 1.37 to 21.85 µM. Simultaneously, these derivatives showed low toxicity towards the pseudonormal human breast epithelial cells of the MCF-10A line (IC50 > 93.01 µM). Les-6287 at 1 µM fully inhibited the formation of colonies of the MCF-7, MDA-MB-231, and HCC1954 cells, while Les-6294 and Les-6328 did that at 2.5 and 5 µM, respectively. Les-6287 suppressed DNA biosynthesis in the MCF-7, MDA-MB-231, and HCC1954 cells. At the same time, such an effect on the MCF-10A cells was significantly lower. Les-6287 induces apoptosis using extrinsic and intrinsic pathways via a decrease in the mitochondrial membrane potential, increasing the activity of caspases 3/7, 8, 9, and 10 in all immunohistochemically different human breast cancer cells. Les-6287 decreased the concentration of the metastasis- and invasion-related proteins MMP-2, MMP-9, and ICAM-1. It did not induce autophagy in treated cells. In conclusion, the results of our study suggest that the synthesized hybrid pyrrolidinedione-thiazolidinones might be promising agents for treating breast tumors of different types.

Genomics in Clinical trials for Breast Cancer

Breast cancer (B.C.) still has increasing incidences and mortality rates globally. It is known that B.C. and other cancers have a very high rate of genetic heterogeneity and genomic mutations. Traditional oncology approaches have not been able to provide a lasting solution. Targeted therapeutics have been instrumental in handling the complexity and resistance associated with B.C. However, the progress of genomic technology has transformed our understanding of the genetic landscape of breast cancer, opening new avenues for improved anti-cancer therapeutics. Genomics is critical in developing tailored therapeutics and identifying patients most benefit from these treatments. The next generation of breast cancer clinical trials has incorporated next-generation sequencing technologies into the process, and we have seen benefits. These innovations have led to the approval of better-targeted therapies for patients with breast cancer. Genomics has a role to play in clinical trials, including genomic tests that have been approved, patient selection and prediction of therapeutic response. Multiple clinical trials in breast cancer have been done and are still ongoing, which have applied genomics technology. Precision medicine can be achieved in breast cancer therapy with increased efforts and advanced genomic studies in this domain. Genomics studies assist with patient outcomes improvement and oncology advancement by providing a deeper understanding of the biology behind breast cancer. This article will examine the present state of genomics in breast cancer clinical trials.

Advanced Hydrogels in Breast Cancer Therapy

Breast cancer is the most common malignancy among women and is the second leading cause of cancer-related death for women. Depending on the tumor grade and stage, breast cancer is primarily treated with surgery and antineoplastic therapy. Direct or indirect side effects, emotional trauma, and unpredictable outcomes accompany these traditional therapies, calling for therapies that could improve the overall treatment and recovery experiences of patients. Hydrogels, biomimetic materials with 3D network structures, have shown great promise for augmenting breast cancer therapy. Hydrogel implants can be made with adipogenic and angiogenic properties for tissue integration. 3D organoids of malignant breast tumors grown in hydrogels retain the physical and genetic characteristics of the native tumors, allowing for post-surgery recapitulation of the diseased tissues for precision medicine assessment of the responsiveness of patient-specific cancers to antineoplastic treatment. Hydrogels can also be used as carrier matrices for delivering chemotherapeutics and immunotherapeutics or as post-surgery prosthetic scaffolds. The hydrogel delivery systems could achieve localized and controlled medication release targeting the tumor site, enhancing efficacy and minimizing the adverse effects of therapeutic agents delivered by traditional procedures. This review aims to summarize the most recent advancements in hydrogel utilization for breast cancer post-surgery tissue reconstruction, tumor modeling, and therapy and discuss their limitations in clinical translation.

Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer

BACKGROUND

Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data.

METHODS

Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively.

RESULTS

The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance.

CONCLUSION

We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.