scholarly journals MicroRNA-1291 Is Associated With Locoregional Metastases in Patients With Early-Stage Breast Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Daniel Escuin ◽  
Laura López-Vilaró ◽  
Olga Bell ◽  
Josefina Mora ◽  
Antonio Moral ◽  
...  

Evidence that microRNAs (miRNAs) regulate the various steps of metastasis is increasing. Several studies have looked at the miRNA expression profile in primary breast tumors but few have compared primary tumor and sentinel lymph node (SLN) metastasis. We correlated the expression of miRNAs with the SLN status and the outcome of axillary lymph node dissection (ALND) in 60 patients with early breast cancer. We profiled the expression of miRNAs in paired breast tumor samples and SLNs using the NextSeq500 Illumina platform and key findings were validated by qPCR. MultiMiR Bioconductor and Reactome pathways analysis were performed to identify target genes and signaling pathways affected by altered expressed miRNAs. Our results show that nine miRNAs were differentially expressed in tumor tissues (q ≤ 0.05). In tumor samples, a 13.5-fold up-regulation of miR-7641-2 (q < 0.001) and a 2.9-fold down-regulation of miR-1291 (q < 0.001) were associated with tumors with positive SLNs. However, only down-regulation of miR-1291 (q = 0.048) remained significant in paired SLNs samples. Interestingly, a 10.5 up-regulation of miR-1291 in SLNs samples was associated with additional axillary lymph node involvement (q < 0.001). The enrichment analyses showed that canonical and non-canonical WNT pathways and negative regulation of various receptor tyrosine kinases signaling pathways were targets of miR-1291 and supports the role of miR-1291 as a tumor suppressor gene (TSG). Further studies are warranted to investigate the use of miR-1291 as a surrogate biomarker of SLN node metastasis in patients with early-stage breast cancer.

The Breast ◽  
2019 ◽  
Vol 45 ◽  
pp. 89-96 ◽  
Author(s):  
Carlos A. Garcia-Etienne ◽  
Robert E. Mansel ◽  
Mariano Tomatis ◽  
Joerg Heil ◽  
Laura Biganzoli ◽  
...  

Cancer ◽  
2011 ◽  
Vol 118 (6) ◽  
pp. 1507-1514 ◽  
Author(s):  
Yun Wu ◽  
Elizabeth A. Mittendorf ◽  
Canan Kelten ◽  
Susan L. Tucker ◽  
Wei Wei ◽  
...  

2020 ◽  
Author(s):  
Meng Jiang ◽  
Chang-Li Li ◽  
Rui-Xue Chen ◽  
Shi-Chu Tang ◽  
Xiao-Mao Luo ◽  
...  

Abstract Background: Accurate prediction of axillary lymph node (ALN) involvement in early-stage breast cancer is important for determining appropriate axillary treatment and therefore avoiding unnecessary axillary surgery and complications. This study aimed to develop and validate an ultrasound radiomics nomogram for preoperative evaluation of the ALN burden. Methods: Data of 303 patients from Wuhan Tongji Hospital (training cohort) and 130 cases from Hunan Provincial Tumour Hospital (external validation cohort) between Jun 2016 and May 2019 were enrolled. Radiomic features were extracted from shear-wave elastography (SWE) and corresponding B-mode ultrasound (BMUS) images. Then, the minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) algorithm were used to select ALN status-related features and construct the SWE and BMUS radiomic signatures. Proportional odds ordinal logistic regression was performed using the radiomic signature together with clinical data, and an ordinal nomogram was subsequently developed. We evaluated the performance of the nomogram using C-index, calibration, and compared it with clinical model.Results: Multivariate analysis indicated that SWE signature, US-reported LN status and molecular subtype were independent risk factors associated with ALN status. The radiomics nomogram based on these variables showed good calibration and discrimination in the training set (overall C-index: 0.842; 95%CI, 0.773–0.879) and the validation set (overall C-index: 0.822; 95%CI, 0.765–0.838). For discriminating between disease-free axilla (N0) and any axillary metastasis (N + (≥1)), it achieved C-index of 0.845 (95%CI, 0.777–0.914) for the training cohort and 0.817 (95%CI, 0.769–0.865) for the validation cohort. The tool could also discriminate between low (N + (1–2)) and heavy metastatic burden of ALN (N + (≥3)), with C-index of 0.827 (95%CI, 0.742–0.913) for the training cohort and 0.810 (95%CI, 0.755–0.864) for the validation cohort. Conclusions: The presented radiomics nomogram shows favourable predictive ability for ALN staging in patients with early-stage breast cancer, which could provide incremental information for preoperative decision-making.


Radiology ◽  
2018 ◽  
Vol 288 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Ga Ram Kim ◽  
Ji Soo Choi ◽  
Boo-Kyung Han ◽  
Jeong Eon Lee ◽  
Seok Jin Nam ◽  
...  

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