Association of −2549 Insertion/Deletion Polymorphism of Vascular Endothelial Growth Factor with Breast Cancer in North Indian Patients

Kapahi, Ruhi; Manjari, Mridu; Uppal, Manjit Singh; Singh, Neeti Rajan; Sambyal, Vasudha; Guleria, Kamlesh

doi:10.1089/gtmb.2012.0222

Cited by 23 publications

(17 citation statements)

References 69 publications

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“…In accordance with our results, some studies in humans have shown that serum VEGF levels were higher in patients with breast cancer when compared to healthy subjects and inversely correlated with survival (46,47). On the other hand, Duranyildiz et al (48) and El Tarhouny et al (49) did not observe any significant difference between serum VEGF levels in patients with breast cancer and the control group.…”

Section: Discussionsupporting

confidence: 92%

Prognostic value of vascular endothelial growth factor and hypoxia-inducible factor 1α in canine malignant mammary tumors

et al. 2015

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Section: Discussionsupporting

confidence: 92%

Prognostic value of vascular endothelial growth factor and hypoxia-inducible factor 1α in canine malignant mammary tumors

et al. 2015

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“…NCOA1 promotes angiogenesis in breast tumors by enhancing the transcription of VEGFa via HIFα and AP-1 [95]. Previous studies from our lab on breast cancer patients from same region have reported association of VEGF polymorphisms +405C>G, +936C>T, -2549 Insertion/Deletion, −152G/A, −116G/A, −165C/T and −141A/C with breast cancer risk but no association of VEGF -417C/T, -172C/A and -160C/T and HIF1α polymorphisms (g.C111A, g.C1772T and g.G1790A) with breast cancer risk [96][97][98][99].…”

Section: Discussionmentioning

confidence: 82%

In silico pathway analysis based on Chromosomal Instability in Breast Cancer Patients

KOUR

Sambyal

Guleria

et al. 2020

Preprint

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Background: Complex genomic changes that arise in tumors are a consequence of chromosomal instability. In tumor cells genomic aberrations disrupt core signaling pathways involving various genes, thus delineating of signaling pathways can help understand the pathogenesis of cancer. The bioinformatics tools can further help in identifying networks of interactions between the genes to get a greater biological context of all genes affected by chromosomal instability. Methods: Karyotypic analyses was done in 150 clinically confirmed breast cancer patients and 150 age and gender matched healthy controls after 72 hours Peripheral lymphocyte culturing and GTG-banding. Reactome database from Cytoscape software version 3.7.1 was used to perform. in-silico analysis (functional interaction and gene enrichment).Results: Frequency of chromosomal aberrations (structural and numerical) was found to be significantly higher in patients as compared to controls. The genes harbored by chromosomal regions showing increased aberration frequency in patients were further analyzed in-silico. Pathway analysis on a set of genes that were not linked together revealed that genes HDAC3, NCOA1, NLRC4, COL1A1, RARA, WWTR1, and BRCA1 were enriched in the RNA Polymerase II Transcription pathway which is involved in recruitment, initiation, elongation and dissociation during transcription. Conclusion: The current study employs the information inferred from chromosomal instability analysis in a non-target tissue for determining the genes and the pathways associated with breast cancer. These results can be further extrapolated by performing either mutation analysis in the genes/pathways deduced or expression analysis which can pinpoint the relevant functional impact of chromosomal instability.

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“…Insertion/Deletion, −152G/A, −116G/A, −165C/T and −141A/C with breast cancer risk but no association of VEGF -417C/T, -172C/A and -160C/T and HIF1α polymorphisms (g.C111A, g.C1772T and g.G1790A) with breast cancer risk [96][97][98][99].…”

Section: Discussionmentioning

confidence: 90%

In silico pathway analysis based on Chromosomal Instability in Breast Cancer Patients

KOUR

Sambyal

Guleria

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Complex genomic changes that arise in tumors are a consequence of chromosomal instability. In tumor cells genomic aberrations disrupt core signaling pathways involving various genes, thus delineating of signaling pathways can help understand the pathogenesis of cancer. The bioinformatics tools can further help in identifying networks of interactions between the genes to get a greater biological context of all genes affected by chromosomal instability. Results: Karyotypic analyses was done in 150 clinically confirmed breast cancer patients and 150 age and gender matched healthy controls after 72 hours Peripheral lymphocyte culturing and GTG-banding. Karyotypic analyses found more frequent chromosomal aberrations (structural and numerical) on chromosome 1, 2, 3, 4, 5, 8, 9, 17 and X. The data of genes harbored by chromosomal regions showing increased aberration frequency was retrieved from online databases. Pathway analysis on a set of genes that were not linked together revealed that genes HDAC3, NCOA1, NLRC4, COL1A1, RARA, WWTR1, and BRCA1 were enriched in the RNA Polymerase II Transcription pathway which is involved in recruitment, initiation, elongation and dissociation during transcription. Conclusion: The chromosomal instability analysis in a non-target in cancer patients thus can be used to identify genes and decipher the pathway involved in tumorigenesis. The bioinformatics approach can help in identifying aberrant genes in transcription pathways and their relation with breast cancer progression.

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Association of −2549 Insertion/Deletion Polymorphism of Vascular Endothelial Growth Factor with Breast Cancer in North Indian Patients

Cited by 23 publications

References 69 publications

Prognostic value of vascular endothelial growth factor and hypoxia-inducible factor 1α in canine malignant mammary tumors

Prognostic value of vascular endothelial growth factor and hypoxia-inducible factor 1α in canine malignant mammary tumors

In silico pathway analysis based on Chromosomal Instability in Breast Cancer Patients

In silico pathway analysis based on Chromosomal Instability in Breast Cancer Patients

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