Curtailing Overexpression of E2F3 in Breast Cancer Using siRNA (E2F3)-Based Gene Silencing

Vimala, K.; Kannan, R.; Sujitha, Mohanan V.; Kannan, Soundarapandian

doi:10.1016/j.arcmed.2012.08.009

Cited by 32 publications

(26 citation statements)

References 23 publications

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“…Furthermore, DEK overexpression may confer stem cell‐like properties on cancer cells that facilitate tumour progression and chemoresistance, demonstrating its importance as a tumour‐initiating oncogene. E2F3 is gained and overexpressed in bladder, prostate, lung and breast cancers, and small interfering RNA‐mediated knockdown of E2F3 in bladder, prostate and breast cancer cells significantly reduced their proliferative capacity. These results point to inactivation of E2F3 as an attractive therapeutic target in multiple cancers …”

Section: Recurrent Gains and Losses Reveal Candidate Oncogenes And Tumentioning

confidence: 99%

“…E2F3 is gained and overexpressed in bladder, prostate, lung and breast cancers, and small interfering RNA‐mediated knockdown of E2F3 in bladder, prostate and breast cancer cells significantly reduced their proliferative capacity. These results point to inactivation of E2F3 as an attractive therapeutic target in multiple cancers …”

Section: Recurrent Gains and Losses Reveal Candidate Oncogenes And Tumentioning

confidence: 99%

“…These results point to inactivation of E2F3 as an attractive therapeutic target in multiple cancers. 70,71…”

Section: Dek -Oncogene Dna Binding (6p223) and E2f3 -E2f Transcripmentioning

confidence: 99%

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The genomic landscape of retinoblastoma: a review

Thériault

Dimaras

Gallie

et al. 2013

Clinical Exper Ophthalmology

166

131

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Retinoblastoma is a paediatric ocular tumour that continues to reveal much about the genetic basis of cancer development. Study of genomic aberrations in retinoblastoma tumours has exposed important mechanisms of cancer development, and identified oncogenes and tumour suppressors that offer potential points of therapeutic intervention. The recent development of next-generation genomic technologies has allowed further refinement of the genomic landscape of retinoblastoma at high resolution. In a relatively short period of time, a wealth of genetic and epigenetic data has emerged on a small number of tumour samples. These data highlight the inherent molecular complexity of this cancer, despite the fact that most retinoblastomas are initiated by the inactivation of a single tumour suppressor gene. Here, we review the current understanding of the genomic, genetic and epigenetic changes in retinoblastoma, highlighting recent genome-wide analyses that have identified exciting candidate genes worthy of further validation as potential prognostic and therapeutic targets.

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Section: Recurrent Gains and Losses Reveal Candidate Oncogenes And Tumentioning

confidence: 99%

Section: Recurrent Gains and Losses Reveal Candidate Oncogenes And Tumentioning

confidence: 99%

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The genomic landscape of retinoblastoma: a review

Thériault

Dimaras

Gallie

et al. 2013

Clinical Exper Ophthalmology

166

131

View full text Add to dashboard Cite

show abstract

“…With these criteria, the genes not yet fully characterized among the top-ranked ones are PTTG1, TEAD4, E2F3, TFDP1, and CEBPG. While PTTG1, TEAD4, E2F3, TFDP1 have been studied to different degrees in BC, C/EBPG was mainly characterized in myeloid tumors (Huggins et al, 2016;Melchor et al, 2009;Vimala, Sundarraj, Sujitha, & Kannan, 2012;Wang et al, 2015;Yoon et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Network analysis allows to unravel breast cancer molecular features and to identify novel targets

Savino

Avalle

Monteleone

et al. 2019

Preprint

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The behaviour of complex biological systems is determined by the orchestrated activity of many components interacting with each other, and can be investigated by networks. In particular, gene co-expression networks have been widely used in the past years thanks to the increasing availability of huge gene expression databases. Breast cancer is a heterogeneous disease usually classified either according to immunohistochemical features or by expression profiling, which identifies the 5 subtypes luminal A, luminal B, basal-like, HER2-positive and normal-like. Basal-like tumours are the most aggressive subtype, for which so far no targeted therapy is available.Making use of the WGCNA clustering method to reconstruct breast cancer transcriptional networks from the METABRIC breast cancer dataset, we developed a platform to address specific questions related to breast cancer biology. In particular, we obtained gene modules significantly correlated with survival and age of onset, useful to understand how molecular features and gene expression patterns are organized in breast cancer. We next generated subtype-specific gene networks and in particular identified two modules that are significantly more connected in basallike breast cancer with respect to all other subtypes, suggesting relevant biological functions. We demonstrate that network centrality (kWithin) is a suitable measure to identify relevant genes, since we could show that it correlates with clinical features and that it provides a mean to select potential upstream regulators of a module with high reliability. Finally, we showed the feasibility of adding meaning to the networks by combining them with independently obtained data related to activated pathways.In conclusion, our platform allows to identify groups of genes highly relevant in breast cancer and possibly amenable to drug targeting, due to their ability to regulate survival-related gene networks. This approach could be successfully extended to other BC subtypes, and to all tumor types for which enough expression data are available.

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“…E2F3 is a transcriptional activator which promotes cell cycle progression due to its overexpression in many bladder, lung and prostate cancers [72, reference for RT-PCR and westerns]. siRNA against E2F3 has been shown to block its expression significantly and is a potential therapeutic target in the treatment of breast cancer [38]. …”

Section: Sirna For Breast Cancer Therapymentioning

confidence: 99%

Non-viral nanocarriers for siRNA delivery in breast cancer

Zhang

Huang

2014

Journal of Controlled Release

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Breast cancer is the most frequently diagnosed malignancy in American women. While significant progress has been made in development of modern diagnostic tools and surgical treatments, only marginal improvements have been achieved with relapsed metastatic breast cancer. Small interfering RNAs (siRNAs) mediate gene silencing of a target protein by disrupting messenger RNAs in an efficient and sequence-specific manner. One application of this technology is the knockdown of genes responsible for tumorigenesis, including those driving oncogenesis, survival, proliferation and death of cells, angiogenesis, invasion and metastasis, and resistance to treatment. Non-viral nanocarriers have attracted attention based on their potential for targeted delivery of siRNA and efficient gene silencing without toxicity. Here, we review promising, non-viral delivery strategies employing liposomes, nanoparticles and inorganic materials in breast cancer.

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Curtailing Overexpression of E2F3 in Breast Cancer Using siRNA (E2F3)-Based Gene Silencing

Cited by 32 publications

References 23 publications

The genomic landscape of retinoblastoma: a review

The genomic landscape of retinoblastoma: a review

Network analysis allows to unravel breast cancer molecular features and to identify novel targets

Non-viral nanocarriers for siRNA delivery in breast cancer

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