» Articles » PMID: 32269923

Quantitative Shear Wave Elastography in Primary Invasive Breast Cancers, Based on Collagen-S100A4 Pathology, Indicates Axillary Lymph Node Metastasis

Overview
Specialty Radiology
Date 2020 Apr 10
PMID 32269923
Citations 16
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The purpose of this study was to evaluate the value of quantitative shear wave elastography (SWE) in indicating the axillary lymph node metastasis (LNM) of invasive breast cancers (IBCs) and to investigate if S100A4 plays a key role in promoting metastasis and increasing stiffness in IBC.

Methods: The differences in SWE of 223 IBC patients were compared between the LNM+ and LNM- groups and the optimal cutoff values of SWE for diagnosing LNM were calculated. We searched the gene expression omnibus (GEO) to determine whether S100A4 was more highly expressed in IBCs that were LNM+ than in those that were LNM-. Sirius red and immunohistochemical staining were used to examine the collagen deposition and S100A4 expression of included tissue samples, and correlations of SWE and S100A4 expression with collagen deposition were analyzed.

Results: The optimal cutoff values for Emax (the maximum stiff value), Emean (the mean stiff value), and EmeanR (the ratio of Emean between mass and parenchyma) for diagnosing axillary LNM were 111.05 kPa, 79.80 kPa, and 6.89, respectively. GSE9893 exhibited more increased S100A4 expression in IBCs that were LNM+ than in those that were LNM-. Collagen volume fraction (CVF) and the average optical density of S100A4 (AOD) in the LNM+ group were significantly higher than those in the LNM- group. Emax, Emean, EmeanR, and AOD were all positively correlated with CVF.

Conclusions: SWE in primary IBC could be useful for indicating axillary LNM. S100A4 may be a factor that regulates cancer-associated collagen deposition and metastasis; however, prospective molecular biological studies are needed.

Citing Articles

The correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis.

Xu S, Wang Q, Hong Z Front Oncol. 2024; 14:1433872.

PMID: 39529837 PMC: 11552536. DOI: 10.3389/fonc.2024.1433872.


Comparing shear wave elastography of breast tumors and axillary nodes in the axillary assessment after neoadjuvant chemotherapy in patients with node-positive breast cancer.

Huang J, Liu F, Sun L, Ma C, Fu J, Wang X Radiol Med. 2024; 129(8):1143-1155.

PMID: 39060887 PMC: 11322251. DOI: 10.1007/s11547-024-01848-1.


ANXA9 facilitates S100A4 and promotes breast cancer progression through modulating STAT3 pathway.

Zhou X, Zhao J, Yan T, Ye D, Wang Y, Zhou B Cell Death Dis. 2024; 15(4):260.

PMID: 38609357 PMC: 11014919. DOI: 10.1038/s41419-024-06643-4.


Investigation of correlation between shear wave elastography and lymphangiogenesis in invasive breast cancer and diagnosis of axillary lymph node metastasis.

Li B, Dai S, Wang Q, Jing H, Shao H, Zhang L BMC Cancer. 2024; 24(1):409.

PMID: 38566057 PMC: 10986065. DOI: 10.1186/s12885-024-12115-x.


Ultrasound in the Diagnosis of Non-Expandable Lung: A Prospective Observational Study of M-Mode, B-Mode, and 2D-Shear Wave Elastography.

Petersen J, Fjaellegaard K, Rasmussen D, Alstrup G, Hoegholm A, Sidhu J Diagnostics (Basel). 2024; 14(2).

PMID: 38248080 PMC: 10813923. DOI: 10.3390/diagnostics14020204.


References
1.
Pankratova S, Klingelhofer J, Dmytriyeva O, Owczarek S, Renziehausen A, Syed N . The S100A4 Protein Signals through the ErbB4 Receptor to Promote Neuronal Survival. Theranostics. 2018; 8(14):3977-3990. PMC: 6071530. DOI: 10.7150/thno.22274. View

2.
Ishikawa M, Osaki M, Yamagishi M, Onuma K, Ito H, Okada F . Correlation of two distinct metastasis-associated proteins, MTA1 and S100A4, in angiogenesis for promoting tumor growth. Oncogene. 2019; 38(24):4715-4728. DOI: 10.1038/s41388-019-0748-z. View

3.
Acerbi I, Cassereau L, Dean I, Shi Q, Au A, Park C . Human breast cancer invasion and aggression correlates with ECM stiffening and immune cell infiltration. Integr Biol (Camb). 2015; 7(10):1120-34. PMC: 4593730. DOI: 10.1039/c5ib00040h. View

4.
Gabriel E, Attwood K, Young J, Cappuccino H, Kumar S . Impact of American College of Surgeons Oncology Group Z11 on surgical training at an academic cancer center. J Surg Res. 2016; 201(2):266-71. PMC: 5315694. DOI: 10.1016/j.jss.2015.11.014. View

5.
Anvari A, Halpern E, Samir A . Essentials of Statistical Methods for Assessing Reliability and Agreement in Quantitative Imaging. Acad Radiol. 2017; 25(3):391-396. PMC: 5834361. DOI: 10.1016/j.acra.2017.09.010. View