Heterogeneity of Tumors in Breast Cancer: Implications and Prospects for Prognosis and Therapeutics

Navigating the Intricacies of Tumor Heterogeneity: An Insight into Potential Prognostic Breast Cancer Biomarkers

Breast cancer is a heterogeneous disease with diverse histological and molecular subtypes. Luminal breast tumors are the most diagnosed subtype. In luminal breast cancer, hormone receptors (including ER, PR, HER2) play a diagnostic and prognostic role. Despite the effectiveness of endocrine therapy in luminal breast tumors, tumor recurrence and resistance occur, and this may highlight evolutionary strategies for survival driven by stemness. In this review we thus consider the association between estrogen signaling and stemness in mediating tumor processes. Many studies report stemness as one of the factors promoting tumor progression. Its association with estrogen signaling warrants further investigation and provides an opportunity for the identification of novel biomarkers which may be used for diagnostic, prognostic, and therapeutic purposes. Breast cancer stem cells have been characterized (CD44+ CD24-) and their role in promoting treatment resistance and tumor recurrence widely studied; however, the complexity of tumor progression which also involve microenvironmental factors suggests the existence of more varied cell phenotypes which mediate stemness and its role in tumor progression.

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

OBJECTIVE

To explore the relationships between S100A7 and the immune characteristics, tumor heterogeneity, and tumor stemness pan-cancer as well as the effect of S100A7 on chemotherapy sensitivity in breast cancer.

METHODS

TCGA-BRCA and TCGA-PANCANCER RNA-seq data and clinical follow-up survival data were collected from the University of California Santa Cruz database. Survival analyses were performed to explore the relationship between S100A7 expression and pan-cancer prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and Gene Set Enrichment Analysis (GSEA) were used to identify the potential pathways related to the differentially expressed genes in breast cancer. Spearman's and Wilcoxon's tests were used to investigate the relationships between S100A7 expression and immune characteristics, methylation, tumor heterogeneity, and tumor stemness. The potential functions of S100A7 and its influence on chemotherapy sensitivity in breast cancer were elucidated using reverse transcription-quantitative PCR, Cell Counting Kit-8 (CCK-8) assay, Transwell assay, and wound healing assay.

RESULTS

S100A7 was highly expressed in most types of tumors and was associated with poor prognosis. S100A7 was closely associated with immunomodulators, immune checkpoint and immune cell infiltration. Further, S100A7 was related to tumor mutational burden, tumor heterogeneity, methylation and tumor stemness in breast cancer. High S100A7 expression was associated with the invasiveness, migration, proliferation and chemotherapy resistance of breast cancer cells in vitro experiments.

CONCLUSION

High S100A7 expression was related with poor prognosis and chemotherapy resistance in breast cancer, making it a potential immune and chemotherapy resistance biomarker.

Anti-breast cancer activity of biosynthesized selenium nanoparticles using Bacillus coagulans supernatant

BACKGROUND

In the present study, Selenium Nanoparticles (SeNPs) were prepared using Bacillus coagulans, which is a type of Lactic Acid Bacteria (LAB), and then they were applied to treat breast cancer cells.

METHODS

The chemicophysical properties of the bioengineered SeNPs were investigated by Transmission Electron Microscopy (TEM), Field Emission Scanning Electron Microscopy (FE-SEM), zeta potential, dynamic light scattering, Fourier Transform Infrared Spectroscopy (FT-IR), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction analysis (XRD). The cytotoxic potential of SeNPs was evaluated by MTT assay against MCF-7 breast cancer cell line. The expression levels of apoptotic genes including BAX, BCL2, VEGF, ERBB2, CASP3, CASP9, CCNE1, CCND1, MMP2 and MMP9 were determined by real-time PCR. The rate of apoptosis and necrosis of the cancer cells as well as the results of the cell cycle were evaluated by flow cytometry method.

RESULTS

The synthesized SeNPs had an average particle size of about 24-40 nm and a zeta potential of -16.1 mV, indicating the high stability of SeNPs. EDX results showed presence of SeNPs because amount of selenium in SeNPs was 86.6 % by weight. The cytotoxicity results showed a concentration-dependent effect against MCF-7 cells. The half-maximal inhibitory concentration (IC50) values of B. coagulans supernatant and SeNPs against breast cancer cells were 389.7 µg/mL and 17.56 µg/mL, respectively. In addition, SeNPs synthesized by the green process exhibited enhanced apoptotic potential in MCF-7 cancer cells compared with bacterial supernatants. Cancer cells treated with IC50 concentration of SeNPs induced 32 % apoptosis compared to untreated cells (3 % apoptosis). The gene expression levels of BAX, CASP3, and CASP9 were upregulated, while the expression levels of BCL2, CCNE1, CCND1, MMP2, MMP9, VEGF, and ERBB2 were downregulated after SeNPs treatment of cells. The potential of SeNPs to induce cell apoptosis was demonstrated by the increase in the expression level of BAX gene and the decrease in the expression level of BCL2 after treatment of cancer cells with SeNPs.

CONCLUSION

The obtained results indicated that SeNPs had strong potential to induce significant cell apoptosis and are cytotoxic against the MCF-7 cancer cell line.

Novel immunotherapies for breast cancer: Focus on 2023 findings

Immunotherapy has emerged as a revolutionary approach in cancer therapy, and recent advancements hold significant promise for breast cancer (BCa) management. Employing the patient's immune system to combat BCa has become a focal point in immunotherapeutic investigations. Strategies such as immune checkpoint inhibitors (ICIs), adoptive cell transfer (ACT), and targeting the tumor microenvironment (TME) have disclosed encouraging clinical outcomes. ICIs, particularly programmed cell death protein 1 (PD-1)/PD-L1 inhibitors, exhibit efficacy in specific BCa subtypes, including triple-negative BCa (TNBC) and human epidermal growth factor receptor 2 (HER2)-positive cancers. ACT approaches, including tumor-infiltrating lymphocytes (TILs) and chimeric antigen receptor (CAR) T-cell therapy, showed promising clinical outcomes in enhancing tumor recognition and elimination. Targeting the TME through immune agonists and oncolytic viruses signifies a burgeoning field of research. While challenges persist in patient selection, resistance mechanisms, and combination therapy optimization, these novel immunotherapies hold transformative potential for BCa treatment. Continued research and clinical trials are imperative to refine and implement these innovative approaches, paving the way for improved outcomes and revolutionizing the management of BCa. This review provides a concise overview of the latest immunotherapies (2023 studies) in BCa, highlighting their potential and current status.

Screening of phytochemicals from Clerodendrum inerme (L.) Gaertn as potential anti-breast cancer compounds targeting EGFR: an in-silico approach

Breast cancer (BC) is the most prevalent malignancy among women around the world. The epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor (RTK) of the ErbB/HER family. It is essential for triggering the cellular signaling cascades that control cell growth and survival. However, perturbations in EGFR signaling lead to cancer development and progression. Hence, EGFR is regarded as a prominent therapeutic target for breast cancer. Therefore, in the current investigation, EGFR was targeted with phytochemicals from Clerodendrum inerme (L.) Gaertn (C. inerme). A total of 121 phytochemicals identified by gas chromatography-mass spectrometry (GC-MS) analysis were screened against EGFR through molecular docking, ADMET analyses (Absorption, Distribution, Metabolism, Excretion, and Toxicity), PASS predictions, and molecular dynamics simulation, which revealed three potential hit compounds with CIDs 10586 [i.e. alpha-bisabolol (-6.4 kcal/mol)], 550281 [i.e. 2,(4,4-Trimethyl-3-hydroxymethyl-5a-(3-methyl-but-2-enyl)-cyclohexene) (-6.5 kcal/mol)], and 161271 [i.e. salvigenin (-7.4 kcal/mol)]. The FDA-approved drug gefitinib was used to compare the inhibitory effects of the phytochemicals. The top selected compounds exhibited good ADMET properties and obeyed Lipinski's rule of five (ROF). The molecular docking analysis showed that salvigenin was the best among the three compounds and formed bonds with the key residue Met 793. Furthermore, the molecular mechanics generalized born surface area (MMGBSA) calculations, molecular dynamics simulation, and normal mode analysis validated the binding affinity of the compounds and also revealed the strong stability and compactness of phytochemicals at the docked site. Additionally, DFT and DOS analyses were done to study the reactivity of the compounds and to further validate the selected phytochemicals. These results suggest that the identified phytochemicals possess high inhibitory potential against the target EGFR and can treat breast cancer. However, further in vitro and in vivo investigations are warranted towards the development of these constituents into novel anti-cancer drugs.Communicated by Ramaswamy H. Sarma.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A Retrospective Single-Center Study

This study aimed to explore the potential of multi-phase dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomics for classifying breast cancer surrogate subtypes. This retrospective study analyzed 360 breast cancers from 319 patients who underwent pretreatment DCE-MRI between January 2015 and January 2019. The cohort consisted of 33 triple-negative, 26 human epidermal growth factor receptor 2 (HER2)-positive, 109 luminal A-like, 144 luminal B-like HER2-negative, and 48 luminal B-like HER2-positive lesions. A total of 1781 radiomic features were extracted from manually segmented breast cancers in each DCE-MRI sequence. The model was internally validated and selected using ten times repeated five-fold cross-validation on the primary cohort, with further evaluation using a validation cohort. The most successful models were logistic regression models applied to the third post-contrast subtraction images. These models exhibited the highest area under the curve (AUC) for discriminating between luminal A like vs. others (AUC: 0.78), luminal B-like HER2 negative vs. others (AUC: 0.57), luminal B-like HER2 positive vs. others (AUC: 0.60), HER2 positive vs. others (AUC: 0.81), and triple negative vs. others (AUC: 0.83). In conclusion, the radiomic features extracted from multi-phase DCE-MRI are promising for discriminating between breast cancer subtypes. The best-performing models relied on tissue changes observed during the mid-stage of the imaging process.

Organic Nanodelivery Systems as a New Platform in the Management of Breast Cancer: A Comprehensive Review from Preclinical to Clinical Studies

Breast cancer accounts for approximately 25% of cancer cases and 16.5% of cancer deaths in women, and the World Health Organization predicts that the number of new cases will increase by almost 70% over the next two decades, mainly due to an ageing population. Effective diagnostic and treatment strategies are, therefore, urgently required for improving cure rates among patients since current therapeutic modalities have many limitations and side effects. Nanomedicine is evolving as a promising approach for cancer management, including breast cancer, and various types of organic and inorganic nanomaterials have been investigated for their role in breast cancer diagnosis and treatment. Following an overview on breast cancer characteristics and pathogenesis and challenges of the current treatment strategies, the therapeutic potential of biocompatible organic-based nanoparticles such as liposomes and polymeric micelles that have been tested in breast cancer models are reviewed. The efficacies of different drug delivery and targeting strategies are documented, ranging from synthetic to cell-derived nanoformulations together with a summary of the interaction of nanoparticles with externally applied energy such as radiotherapy. The clinical translation of nanoformulations for breast cancer treatment is summarized including those undergoing clinical trials.

Addressing the Clinical Feasibility of Adopting Circulating miRNA for Breast Cancer Detection, Monitoring and Management with Artificial Intelligence and Machine Learning Platforms

Detecting breast cancer (BC) at the initial stages of progression has always been regarded as a lifesaving intervention. With modern technology, extensive studies have unraveled the complexity of BC, but the current standard practice of early breast cancer screening and clinical management of cancer progression is still heavily dependent on tissue biopsies, which are invasive and limited in capturing definitive cancer signatures for more comprehensive applications to improve outcomes in BC care and treatments. In recent years, reviews and studies have shown that liquid biopsies in the form of blood, containing free circulating and exosomal microRNAs (miRNAs), have become increasingly evident as a potential minimally invasive alternative to tissue biopsy or as a complement to biomarkers in assessing and classifying BC. As such, in this review, the potential of miRNAs as the key BC signatures in liquid biopsy are addressed, including the role of artificial intelligence (AI) and machine learning platforms (ML), in capitalizing on the big data of miRNA for a more comprehensive assessment of the cancer, leading to practical clinical utility in BC management.

Annexin A2 (AnxA2) association with the clinicopathological data in different breast cancer subtypes: A possible role for AnxA2 in tumor heterogeneity and cancer progression

BACKGROUND

Breast cancer is a highly heterogeneous type of neoplasia with molecular and biochemical alterations in the ductal epithelium. AnxA2 has a diverse functions and through intracellular interaction with other molecules promotes carcinogenesis.

AIMS

To study the possible involvement of AnxA2 in breast cancer heterogeneity and cancer progression.

PATIENTS AND METHODS

Tumor tissue and serum were obtained from different breast cancer subtypes. Tumor tissues were processed for histopathological studies. AnxA2 levels were assessed in the tissues by H scoring and in the serum by ELISA. AnxA2 levels were correlated with HER2 and Ki67 and with clinicopathological data. Normal breast tissues and serum from healthy subjects were used as controls.

RESULTS

AnxA2 showed a peculiar distribution in tumor tissues and nearby interstitial tissues. Pattern of expressions varied in different subtypes with the highest expression in triple negative subtype. Tissue and serum AnxA2 showed significant co-upregulations in breast cancer. Moreover, they showed positive correlations with HER2 and Ki67 and associations with clinicopathological data including cancer staging and lymph node metastasis.

CONCLUSION

For the best of our knowledge this is the first study showing correlation between AnxA2, the proposed prognostic marker and the well-established tumor markers; HER2 and Ki67. AnxA2 might contribute to breast cancer heterogeneity and is associated with poor prognosis. AnxA2 might be a prognostic marker and an additional marker for breast cancer grading and clinical staging. Interestingly, tissue and serum AnxA2 showed a strong correlation. Thus, assessing serum AnxA2 can be a noninvasive prognostic tool.

The Reduced Graphene Oxide (rGO) Induces Apoptosis, Autophagy and Cell Cycle Arrest in Breast Cancer Cells

Reduced graphene oxide (rGO) has already been reported as a potential cytostatic agent in various cancers. However, the mechanisms underlying rGO’s cytotoxicity are still insufficiently understood. Thus, the aim of the study was to investigate the molecular and cellular effects of rGO in breast cancer. Given this, two cell lines, MDA-MB-231 and ZR-75-1, were analyzed using MTT test, flow cytometry and Western blot assay. Incubation with rGO resulted in a multitude of effects, including the stimulation of autophagy, cell cycle arrest and, finally, the apoptotic death of cancer cells. Notably, rGO had minimal effect on normal human fibroblasts. Apoptosis in cancer cells was accompanied by decreased mitochondrial membrane potential, the deregulated expression of mitochondrial proteins and the activation of caspase 9 and caspase 3, suggesting that rGO predominantly induced apoptosis via intrinsic pathway. The analysis of LC3 protein expression revealed that rGO also caused autophagy in breast cancer cells. Moreover, rGO treatment resulted in cell cycle arrest, which was accompanied by deregulated p21 expression. Altogether, rGO seems to have multidirectional cytostatic and cytotoxic effects in breast cancer cells, making it a promising agent worthy of further investigation.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Research progress in breast cancer stem cells: characterization and future perspectives

More and more studies have proved that there are a small number of cells with self-renewal and differentiation ability in breast tumors, namely breast cancer stem cells. Such cells play a key role in the initiation, development and migration of breast tumors. The properties of breast tumor stem cells are regulated by a range of intracellular and extracellular factors, including important signaling pathways, transcription factors, non-coding RNAs, and cytokines such as Hedgehog, Wnt, Notch, microRNA93, microRNA100, and IL-6. Tumor microenvironment (such as mesenchymal stem cells, macrophages and cytokines) plays an important role in the regulation of breast tumor stem cells. Using the keywords including "breast cancer stem cells", "signal pathway", "chemotherapy tolerance", and "non-coding RNA", "triple negative breast cancer", "inhibitors", this study retrieved the original articles and reviews published before October 3, 2021, from PubMed and WEB OF SCI database and this study performed a comprehensive review of them. After treatment, there is a correlation between the metastasis-prone nature and recurrence with breast cancer stem cells. The signaling pathway of breast cancer stem cells plays a significant role in activating the function of breast cancer cells, regulating the differentiation of breast cancer cells and controlling the division of breast cancer cells. This imbalance leads to the uncontrolled growth and development of breast cancer cells. Targeted therapy that blocks the corresponding pathway may become a new perspective for breast cancer treatment. In addition, corresponding therapeutic strategies can be used according to the expression characteristics of different molecular types of breast cancer stem cells. For ER-positive breast cancer, simultaneous endocrine therapy and targeted therapy of tumor stem cells may improve the efficacy of endocrine therapy. Trastuzumab therapy significantly reduces the risk of recurrence of HER2-positive breast cancer. For drug-resistant patients, combination therapy is required due to the different phenotypes of epithelial-mesenchymal transforming tumor stem cells. This study briefly reviews the research progress of breast cancer stem cell-related signaling pathways and their inhibitors, in order to provide a reference for breast cancer patients to obtain more effective clinical treatment.

Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

Breast cancer is a global cause for concern owing to its high incidence around the world. The alarming increase in breast cancer cases emphasizes the management of disease at multiple levels. The management should start from the beginning that includes stringent cancer screening or cancer registry to effective diagnostic and treatment strategies. Breast cancer is highly heterogeneous at morphology as well as molecular levels and needs different therapeutic regimens based on the molecular subtype. Breast cancer patients with respective subtype have different clinical outcome prognoses. Breast cancer heterogeneity emphasizes the advanced molecular testing that will help on-time diagnosis and improved survival. Emerging fields such as liquid biopsy and artificial intelligence would help to under the complexity of breast cancer disease and decide the therapeutic regimen that helps in breast cancer management. In this review, we have discussed various risk factors and advanced technology available for breast cancer diagnosis to combat the worst breast cancer status and areas that need to be focused for the better management of breast cancer.

Activated ERK Signaling Is One of the Major Hub Signals Related to the Acquisition of Radiotherapy-Resistant MDA-MB-231 Breast Cancer Cells

Breast cancer is one of the major causes of deaths due to cancer, especially in women. The crucial barrier for breast cancer treatment is resistance to radiation therapy, one of the important local regional therapies. We previously established and characterized radio-resistant MDA-MB-231 breast cancer cells (RT-R-MDA-MB-231 cells) that harbor a high expression of cancer stem cells (CSCs) and the EMT phenotype. In this study, we performed antibody array analysis to identify the hub signaling mechanism for the radiation resistance of RT-R-MDA-MB-231 cells by comparing parental MDA-MB-231 (p-MDA-MB-231) and RT-R-MDA-MB-231 cells. Antibody array analysis unveiled that the MAPK1 protein was the most upregulated protein in RT-R-MDA-MB-231 cells compared to in p-MDA-MB-231 cells. The pathway enrichment analysis also revealed the presence of MAPK1 in almost all enriched pathways. Thus, we used an MEK/ERK inhibitor, PD98059, to block the MEK/ERK pathway and to identify the role of MAPK1 in the radio-resistance of RT-R-MDA-MB-231 cells. MEK/ERK inhibition induced cell death in both p-MDA-MB-231 and RT-R-MDA-MB-231 cells, but the death mechanism for each cell was different; p-MDA-MB-231 cells underwent apoptosis, showing cell shrinkage and PARP-1 cleavage, while RT-R-MDA-MB-231 cells underwent necroptosis, showing mitochondrial dissipation, nuclear swelling, and an increase in the expressions of CypA and AIF. In addition, MEK/ERK inhibition reversed the radio-resistance of RT-R-MDA-MB-231 cells and suppressed the increased expression of CSC markers (CD44 and OCT3/4) and the EMT phenotype (β-catenin and N-cadherin/E-cadherin). Taken together, this study suggests that activated ERK signaling is one of the major hub signals related to the radio-resistance of MDA-MB-231 breast cancer cells.