Polymeric Delivery of siRNA against Integrin‐β1 (CD29) to Reduce Attachment and Migration of Breast Cancer Cells

Sundaram, Daniel Nisakar Meenakshi; Kucharski, Cezary; Parmar, Manoj B.; Kc, Remant Bahadur; Uludağ, Hasan

doi:10.1002/mabi.201600430

Cited by 13 publications

(18 citation statements)

References 53 publications

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“…Several ECM proteins have been associated with resistance to chemotherapy. Fibronectin has been associated with increased migration of several cancer cells [ 198 , 199 , 200 , 201 ]. Changes in ECM elasticity and stiffness are some of the factors known to affect drug delivery to cancer cells.…”

Section: Tumor Microenvironmentmentioning

confidence: 99%

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Senthebane

Rowe

Thomford

et al. 2017

IJMS

334

330

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Chemoresistance is a leading cause of morbidity and mortality in cancer and it continues to be a challenge in cancer treatment. Chemoresistance is influenced by genetic and epigenetic alterations which affect drug uptake, metabolism and export of drugs at the cellular levels. While most research has focused on tumor cell autonomous mechanisms of chemoresistance, the tumor microenvironment has emerged as a key player in the development of chemoresistance and in malignant progression, thereby influencing the development of novel therapies in clinical oncology. It is not surprising that the study of the tumor microenvironment is now considered to be as important as the study of tumor cells. Recent advances in technological and analytical methods, especially ‘omics’ technologies, has made it possible to identify specific targets in tumor cells and within the tumor microenvironment to eradicate cancer. Tumors need constant support from previously ‘unsupportive’ microenvironments. Novel therapeutic strategies that inhibit such microenvironmental support to tumor cells would reduce chemoresistance and tumor relapse. Such strategies can target stromal cells, proteins released by stromal cells and non-cellular components such as the extracellular matrix (ECM) within the tumor microenvironment. Novel in vitro tumor biology models that recapitulate the in vivo tumor microenvironment such as multicellular tumor spheroids, biomimetic scaffolds and tumor organoids are being developed and are increasing our understanding of cancer cell-microenvironment interactions. This review offers an analysis of recent developments on the role of the tumor microenvironment in the development of chemoresistance and the strategies to overcome microenvironment-mediated chemoresistance. We propose a systematic analysis of the relationship between tumor cells and their respective tumor microenvironments and our data show that, to survive, cancer cells interact closely with tumor microenvironment components such as mesenchymal stem cells and the extracellular matrix.

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Section: Tumor Microenvironmentmentioning

confidence: 99%

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Senthebane

Rowe

Thomford

et al. 2017

IJMS

334

330

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“…The 1.2PEI-Lau8 polymer emerged as the leading candidate from this screen. The same polymer, when previously applied in breast cancer studies, only exhibited moderate performance for siRNA delivery [ 37 ], indicating the need to tailor delivery systems for specific cell phenotypes. The other effective polymer 2PEI-LA6 was successful in other cancer types such as AML, CML and breast cancer [ 25 , 37 – 39 ], indicating a more universal applicability of this delivery system.…”

Section: Discussionmentioning

confidence: 99%

“…The same polymer, when previously applied in breast cancer studies, only exhibited moderate performance for siRNA delivery [ 37 ], indicating the need to tailor delivery systems for specific cell phenotypes. The other effective polymer 2PEI-LA6 was successful in other cancer types such as AML, CML and breast cancer [ 25 , 37 – 39 ], indicating a more universal applicability of this delivery system. The smaller LA derivative of PEI (1.2PEI-LA6) did not demonstrate effective siRNA delivery in both cell lines, presumably due to smaller size and relatively less efficient binding to siRNA; however, in previous reports, the same polymer was able to effectively deliver siRNA to MDA-MB-231 and MCF7 breast cancer cells.…”

Section: Discussionmentioning

confidence: 99%

“…The smaller LA derivative of PEI (1.2PEI-LA6) did not demonstrate effective siRNA delivery in both cell lines, presumably due to smaller size and relatively less efficient binding to siRNA; however, in previous reports, the same polymer was able to effectively deliver siRNA to MDA-MB-231 and MCF7 breast cancer cells. This emphasizes that different polymer formulations might be required for different cell types and the functionality of the same polymer could vary among various cell lines owing to the different cell properties [ 37 , 40 ]. Other studies showed that the efficiency of these polymers was related to their physiochemical characteristics including the optimal degree of lipid substitution, type of the lipid substituent, MW, charge and size of the siRNA nanoparticles [ 28 , 30 , 41 ], which were not repeated in this study.…”

Section: Discussionmentioning

confidence: 99%

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Therapeutic delivery of siRNA with polymeric carriers to down-regulate STAT5A expression in high-risk B-cell acute lymphoblastic leukemia (B-ALL)

et al. 2021

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Overexpression and persistent activation of STAT5 play an important role in the development and progression of acute lymphoblastic leukemia (ALL), the most common pediatric cancer. Small interfering RNA (siRNA)-mediated downregulation of STAT5 represents a promising therapeutic approach for ALL to overcome the limitations of current treatment modalities such as high relapse rates and poor prognosis. However, to effectively transport siRNA molecules to target cells, development of potent carriers is of utmost importance to surpass hurdles of delivery. In this study, we investigated the use of lipopolymers as non-viral delivery systems derived from low molecular weight polyethylenimines (PEI) substituted with lauric acid (Lau), linoleic acid (LA) and stearic acid (StA) to deliver siRNA molecules to ALL cell lines and primary samples. Among the lipid-substituted polymers explored, Lau- and LA-substituted PEI displayed excellent siRNA delivery to SUP-B15 and RS4;11 cells. STAT5A gene expression was downregulated (36–92%) in SUP-B15 and (32%) in RS4;11 cells using the polymeric delivery systems, which consequently reduced cell growth and inhibited the formation of colonies in ALL cells. With regard to ALL primary cells, siRNA-mediated STAT5A gene silencing was observed in four of eight patient cells using our leading polymeric delivery system, 1.2PEI-Lau8, accompanied by the significant reduction in colony formation in three of eight patients. In both BCR-ABL positive and negative groups, three of five patients demonstrated marked cell growth inhibition in both MTT and trypan blue exclusion assays using 1.2PEI-Lau8/siRNA complexes in comparison with their control siRNA groups. Three patient samples did not show any positive results with our delivery systems. Differential therapeutic responses to siRNA therapy observed in different patients could result from variable genetic profiles and patient-to-patient variability in delivery. This study supports the potential of siRNA therapy and the designed lipopolymers as a delivery system in ALL therapy.

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“…The experimental cellular uptake data of PEI/siRNA NPs into various breast cancer cell lines including MDA MB231, MCF7, AU565, MDA 468, MDA 435, and MDA 231 were collected from previous publications by our group. [ 3,21–26 ] All NPs were tested under similar culture conditions in the same laboratory, thereby enabling direct comparisons across NP formulations. The basic methodology remained the same, where a scrambled FAM‐labeled siRNA was formulated with PEI carriers and the uptake determined after 24 h using flow cytometry methodology.…”

Section: Methodsmentioning

confidence: 99%

Modeling Uptake of Polyethylenimine/Short Interfering RNA Nanoparticles in Breast Cancer Cells Using Machine Learning

Nademi

Tang

Uludağ

2021

Advanced NanoBiomed Research

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Polyethylenimine (PEI) is one of the most promising nonviral vectors for delivery of short interfering RNA (siRNA) agents into cancer cells. A promising approach that increases the delivery efficiency of PEI is its modification with hydrophobic substitutions. However, the performance of modified PEIs depends on the nature and extent of substitutions. Herein, machine learning algorithms are used on the basis of quantitative structure activity relationship (QSAR) method to predict the cellular uptake of hydrophobically modified PEI/siRNA nanoparticles (NPs) into various cancer cell lines. To this end, 3 different regression models, namely, random forest (RF), multilayer perceptron (MLP), and linear regression (LR), are used. The results show that RF and MLP regression methods have a better performance than the LR method, suggesting that nonlinear models are better estimators when predicting the cellular uptake of PEI/siRNA NPs. Additionally, critical descriptors that have major contributions to cellular uptake are found to be PEI‐to‐siRNA weight ratio, type of hydrophobic substitution, as well as total numbers of Cs, unsaturated C, and thioester groups on substitutions in each PEI. This study is the first report that predicts cellular uptake with PEI‐based carriers, which provides valuable insight into the design of performance‐enhancing hydrophobic substituents on PEIs.

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Polymeric Delivery of siRNA against Integrin‐β1 (CD29) to Reduce Attachment and Migration of Breast Cancer Cells

Cited by 13 publications

References 53 publications

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Therapeutic delivery of siRNA with polymeric carriers to down-regulate STAT5A expression in high-risk B-cell acute lymphoblastic leukemia (B-ALL)

Modeling Uptake of Polyethylenimine/Short Interfering RNA Nanoparticles in Breast Cancer Cells Using Machine Learning

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