(: MVD) is the quantification method of various aspects of tumor vasculature that indicates angiogenic activity. This study aims to analyze the correlation between MVD to the expression of VEGFRs on breast cancer tissue.
Materials and Method: A total of 60 N-methyl-N-nitrosourea (MNU)-induced breast carcinomas in rats were suppressed by using antiangiogenic drugs. The rats were then sacrificed, and the tumor was fixed in 10% formalin, paraffin embedded, and immunohistochemistry stained using VEGFRs and CD34.
Result: One-way ANOVA test showed a significant difference in all markers that have been used (P < 0.05) on MNU-breast tumor treated with rapamycin (M= 90.1664, SD= 7.4487), PF4 (M= 93.7946, SD= 7.1303) and rapamycin + PF4 (M= 93.6990, SD= 1.8432). We obtained a significant reduction of MVD count on breast carcinoma for rapamycin group (M= 25.6786, SD= 9.7075) and rapamycin + PF4 group (M= 30.5250, SD= 13.6928) while PF4 group (M=47.7985, SD=4.8892) showed slightly increase compared to control (M= 45.1875, SD= 4.4786). There was a moderately strong, positive correlation between angiogenic markers; Flt-1 (r= 0.544, n=60, P < 0.005) and Flt-4 (r= 0.555, n= 60, P < 0.005) while Flk-1 (r= 0.797, n= 60, P < 0.005) showed a strong, positive correlation with MVD.
Conclusion: MVD was strongly correlated to the VEGFRs expression on breast carcinoma.
METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.
METHODS: Blood from 30 patients with primary OSCC and 1:1 age-sex-matched controls was subjected to qPCR and ELISA to detect VEGF-A gene expression and serum level. Tumors of the 30 patients were investigated for VEGF Receptor-2 (VEGFR-2) expression and were analyzed using Image J software version 1.52 for DAB percentage (DAB-P) area and optical density (OD).
RESULTS: VEGF-A relative gene expression among patients was 2.43-fold higher compared to the healthy control group. Well-differentiated had a 1.98-fold increment, while poorly differentiated had a 3.58-fold increment. Serum VEGF-A was significantly elevated among the patients compared to controls (458.7 vs 253.2, p=0.0225). Poorly differentiated had a higher serum VEGF concentration (1262.0±354.7pg/ml) compared with other two. Mean VEGFR-2 DAB-P level in OSCC was 42.41±5.61(p=0.15). Well-differentiated had a DAB-P of 41.20±5.32 while poorly differentiated had DAB-P 46.21±3.78. The mean OD in OSCC was 0.54±0.16. VEGFR-2 OD in well and poorly differentiated OSCC were 0.48±0.12 and 0.68±0.17, respectively.
CONCLUSIONS: VEGF-A gene expression, serum levels, and tissue VEGFR-2 levels correlated linearly with the stage and grade of the tumor. This study justifies the value of VEGF-A as a potential biomarker in OSCC in early detection of OSCC. More studies are needed to accept the use of VEGF-A.