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      Advances with metal oxide-based nanoparticles as MDR metastatic breast cancer therapeutics and diagnostics

      review-article
      RSC Advances
      The Royal Society of Chemistry

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          Abstract

          Metal oxide nanoparticles have attracted increased attention due to their emerging applications in cancer detection and therapy. This study envisioned to highlight the great potential of metal oxide NPs due to their interesting properties including high payload, response to magnetic field, affluence of surface modification to overcome biological barriers, and biocompatibility. Mammogram, ultrasound, X-ray computed tomography (CT), MRI, positron emission tomography (PET), optical or fluorescence imaging are used for breast imaging. Drug-loaded metal oxide nanoparticle delivered to the breast cancer cells leads to higher drug uptake. Thus, enhanced the cytotoxicity to target cells compared to free drug. The drug loaded metal oxide nanoparticle formulations hold great promise to enhance efficacy of breast cancer therapy including multidrug resistant (MDR) and metastatic breast cancers. Various metal oxides including magnetic metal oxides and magnetosomes are of current interests to explore cancer drug delivery and diagnostic efficacy especially for metastatic breast cancer. Metal oxide-based nanocarrier formulations are promising for their usage in drug delivery and release to breast cancer cells, cancer diagnosis and their clinical translations.

          Abstract

          Biomarker targeted therapy approaches for TNBC using metal oxide-based NPs are highly effective and promising.

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          Most cited references203

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          Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies.

          Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted "driver" signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
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            Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.

            The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
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              Targeting hypoxia in cancer therapy.

              Hypoxia is a feature of most tumours, albeit with variable incidence and severity within a given patient population. It is a negative prognostic and predictive factor owing to its multiple contributions to chemoresistance, radioresistance, angiogenesis, vasculogenesis, invasiveness, metastasis, resistance to cell death, altered metabolism and genomic instability. Given its central role in tumour progression and resistance to therapy, tumour hypoxia might well be considered the best validated target that has yet to be exploited in oncology. However, despite an explosion of information on hypoxia, there are still major questions to be addressed if the long-standing goal of exploiting tumour hypoxia is to be realized. Here, we review the two main approaches, namely bioreductive prodrugs and inhibitors of molecular targets upon which hypoxic cell survival depends. We address the particular challenges and opportunities these overlapping strategies present, and discuss the central importance of emerging diagnostic tools for patient stratification in targeting hypoxia.
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                Author and article information

                Journal
                RSC Adv
                RSC Adv
                RA
                RSCACL
                RSC Advances
                The Royal Society of Chemistry
                2046-2069
                17 November 2022
                15 November 2022
                17 November 2022
                : 12
                : 51
                : 32956-32978
                Affiliations
                [a] Department of Chemistry, Shahjalal University of Science and Technology Sylhet 3114 Bangladesh subhan-che@ 123456sust.edu
                Author information
                https://orcid.org/0000-0002-5623-7643
                Article
                d2ra02005j
                10.1039/d2ra02005j
                9670683
                36425155
                4ab9fafd-aa51-4f6d-96a4-0cff177a25d6
                This journal is © The Royal Society of Chemistry
                History
                : 28 March 2022
                : 8 November 2022
                Page count
                Pages: 23
                Categories
                Chemistry
                Custom metadata
                Paginated Article

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