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Association between vascular ultrasound features and DNA sequencing in breast cancer: a preliminary study

Authors :
Mi-Ryung Han
Ah Young Park
Bo Kyoung Seo
Min Sun Bae
Jung Sun Kim
Gil Soo Son
Hye Yoon Lee
Young Woo Chang
Kyu Ran Cho
Sung Eun Song
Ok Hee Woo
Hye-Yeon Ju
Hyunseung Oh
Source :
Discover Oncology. 14
Publication Year :
2023
Publisher :
Springer Science and Business Media LLC, 2023.

Abstract

There are few radiogenomic studies to correlate ultrasound features of breast cancer with genomic changes. We investigated whether vascular ultrasound phenotypes are associated with breast cancer gene profiles for predicting angiogenesis and prognosis. We prospectively correlated quantitative and qualitative features of microvascular ultrasound (vascular index, vessel morphology, distribution, and penetrating vessel) and contrast-enhanced ultrasound (time–intensity curve parameters and enhancement pattern) with genomic characteristics in 31 breast cancers. DNA obtained from breast tumors and normal tissues were analyzed using targeted next-generation sequencing of 105 genes. The single-variant association test was used to identify correlations between vascular ultrasound features and genomic profiles. Chi-square analysis was used to detect single nucleotide polymorphisms (SNPs) associated with ultrasound features by estimating p values and odds ratios (ORs). Eight ultrasound features were significantly associated with 9 SNPs (p ERBB2 (p = 0.04, OR = 7.75); large area under the curve on contrast-enhanced ultrasound with rs35597368 in PDGFRA (p = 0.04, OR = 4.07); high peak intensity with rs35597368 in PDGFRA (p = 0.049, OR = 4.05) and rs2305948 in KDR (p = 0.04, OR = 5.10); and long mean transit time with rs2275237 in ARNT (p = 0.02, OR = 10.25) and rs755793 in FGFR2 (p = 0.02, OR = 10.25). We identified 198 non-silent SNPs in 71 various cancer-related genes. Vascular ultrasound features can reflect genomic changes associated with angiogenesis and prognosis in breast cancer.

Details

ISSN :
27306011
Volume :
14
Database :
OpenAIRE
Journal :
Discover Oncology
Accession number :
edsair.doi...........aab4c675c8b1d6482a840e423f5613bc
Full Text :
https://doi.org/10.1007/s12672-023-00657-8