scholarly journals Exosomes deep sequencing identifies miR-363-5p as a non-invasive biomarker of axillary lymph node metastasis and prognosis in breast cancer

2020 ◽  
Author(s):  
Xin Wang ◽  
Tianyi Qian ◽  
Siqi Bao ◽  
Hengqiang Zhao ◽  
Hongyan Chen ◽  
...  

Abstract Background: Breast cancer is the most common malignant tumor in females. Axillary lymph node (ALN) metastasis is an independent risk factor of prognosis and correlates with distant metastasis. However, the false-negative rate and complications of the standard procedure are not neglectable hitherto. It is necessary to develop an accurate non-invasive approach for lymph node staging.Methods: In this study, circulating exosomal miRNA profiles in peripheral blood from 10 patients with breast cancer and 10 age-matched healthy women were obtained and analyzed using small RNA deep sequencing. Integrative profiles analysis and multiple cross-validation using in-house and external independent datasets were performed to evaluate the diagnostic performance. Functional assays were used to analyze cellular phenotypes and downstream targets of miR-363-5p.Results: We found that the aberrant expression of exosomal miR-363-5p is significantly associated with tumorigenesis (p=0.047) and ALN metastasis (p=0.019). Serum exosomal miR-363-5p demonstrated the consistent down-regulated expression pattern in LN positive patients compared with LN negative patients across multiple independent datasets, which achieved high diagnostic performance in predicting lymph node metastasis (AUC=0.621-0.958). Furthermore, patients with a high expression level of miR-363-5p had significantly improved overall survival (HR=0.63, ±95% CI=0.45-0.89, p=0.0075). Functional experiments discovered that miR-363-5p acts by inhibiting the migration ability of breast cancer cells. Here we further identified Platelet Derived Growth Factor Subunit B (PDGFB) as a downstream target of miR-363-5p.Conclusions: The miR-363-5p deficiency promoted metastasis via facilitating PDGFB expression, leading to overactivity of PDGF signaling in cancer cells. These results demonstrated that tumor metastasis is mediated by tumor-derived exosomes that affect cell growth signal regulation. Therefore, exosomal miR-363-5p may serve as a marker for ALN metastasis diagnosis in a non-invasive manner.


Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 757
Author(s):  
Sanaz Samiei ◽  
Renée W. Y. Granzier ◽  
Abdalla Ibrahim ◽  
Sergey Primakov ◽  
Marc B. I. Lobbes ◽  
...  

Radiomics features may contribute to increased diagnostic performance of MRI in the prediction of axillary lymph node metastasis. The objective of the study was to predict preoperative axillary lymph node metastasis in breast cancer using clinical models and radiomics models based on T2-weighted (T2W) dedicated axillary MRI features with node-by-node analysis. From August 2012 until October 2014, all women who had undergone dedicated axillary 3.0T T2W MRI, followed by axillary surgery, were retrospectively identified, and available clinical data were collected. All axillary lymph nodes were manually delineated on the T2W MR images, and quantitative radiomics features were extracted from the delineated regions. Data were partitioned patient-wise to train 100 models using different splits for the training and validation cohorts to account for multiple lymph nodes per patient and class imbalance. Features were selected in the training cohorts using recursive feature elimination with repeated 5-fold cross-validation, followed by the development of random forest models. The performance of the models was assessed using the area under the curve (AUC). A total of 75 women (median age, 61 years; interquartile range, 51–68 years) with 511 axillary lymph nodes were included. On final pathology, 36 (7%) of the lymph nodes had metastasis. A total of 105 original radiomics features were extracted from the T2W MR images. Each cohort split resulted in a different number of lymph nodes in the training cohorts and a different set of selected features. Performance of the 100 clinical and radiomics models showed a wide range of AUC values between 0.41–0.74 and 0.48–0.89 in the training cohorts, respectively, and between 0.30–0.98 and 0.37–0.99 in the validation cohorts, respectively. With these results, it was not possible to obtain a final prediction model. Clinical characteristics and dedicated axillary MRI-based radiomics with node-by-node analysis did not contribute to the prediction of axillary lymph node metastasis in breast cancer based on data where variations in acquisition and reconstruction parameters were not addressed.



2016 ◽  
Vol 155 (3) ◽  
pp. 615-616 ◽  
Author(s):  
Subir Biswas ◽  
Suman Sengupta ◽  
Sougata Roy Chowdhury ◽  
Samir Jana ◽  
Gunjan Mandal ◽  
...  


2004 ◽  
Vol 87 (2) ◽  
pp. 75-79 ◽  
Author(s):  
Osamu Watanabe ◽  
Tadao Shimizu ◽  
Hiroshi Imamura ◽  
Jun Kinoshita ◽  
Yoshihito Utada ◽  
...  


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