scholarly journals Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review

Tumor Biology ◽  
2017 ◽  
Vol 39 (3) ◽  
pp. 101042831769455 ◽  
Author(s):  
Jia-Mei Chen ◽  
Yan Li ◽  
Jun Xu ◽  
Lei Gong ◽  
Lin-Wei Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Image Features ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Image Feature ◽  
Prognostic Models ◽  
Future Research ◽  
Hematoxylin And Eosin ◽  
Histopathology Images

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature–based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

scholarly journals Roles of the Immune/Methylation/Autophagy Landscape on Single-Cell Genotypes and Stroke Risk in Breast Cancer Microenvironment

2021 ◽  
Vol 2021 ◽  
pp. 1-32
Author(s):  
Jun-yi Wu ◽  
Jun Qin ◽  
Lei Li ◽  
Kun-dong Zhang ◽  
Yi-sheng Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Risk Score ◽  
Cancer Metastasis ◽  
Single Cells ◽  
Cancer Prognosis ◽  
Prognostic Models ◽  
Future Research ◽  
Cancer Microenvironment

This study sought to perform integrative analysis of the immune/methylation/autophagy landscape on breast cancer prognosis and single-cell genotypes. Breast Cancer Recurrence Risk Score (BCRRS) and Breast Cancer Prognostic Risk Score (BCPRS) were determined based on 6 prognostic IMAAGs obtained from the TCGA-BRCA cohort. BCRRS and BCPRS, respectively, were used to construct a risk prediction model of overall survival and progression-free survival. Predictive capacity of the model was evaluated using clinical data. Analysis showed that BCRRS is associated with a high risk of stroke. In addition, PPI and drug-ceRNA networks based on differences in BCPRS were constructed. Single cells were genotyped through integrated scRNA-seq of the TNBC samples based on clustering results of BCPRS-related genes. The findings of this study show the potential regulatory effects of IMAAGs on breast cancer tumor microenvironment. High AUCs of 0.856 and 0.842 were obtained for the OS and PFS prognostic models, respectively. scRNA-seq analysis showed high expression levels of adipocytes and adipose tissue macrophages (ATMs) in high BCPRS clusters. Moreover, analysis of ligand-receptor interactions and potential regulatory mechanisms were performed. The LINC00276&MALAT1/miR-206/FZD4-Wnt7b pathway was also identified which may be useful in future research on targets against breast cancer metastasis and recurrence. Neural network-based deep learning models using BCPRS-related genes showed that these genes can be used to map the tumor microenvironment. In summary, analysis of IMAAGs, BCPRS, and BCRRS provides information on the breast cancer microenvironment at both the macro- and microlevels and provides a basis for development of personalized treatment therapy.

scholarly journals Influence of tumor location on breast cancer prognosis

2003 ◽  
Vol 105 (4) ◽  
pp. 542-545 ◽  
Author(s):  
Niels Kroman ◽  
Jan Wohlfahrt ◽  
Henning T. Mouridsen ◽  
Mads Melbye
Keyword(s):  
Breast Cancer ◽  
Tumor Location ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis

New markers for breast cancer prognosis

1993 ◽  
Vol 47 (6-7) ◽  
pp. 256
Author(s):  
F. Di Carlo ◽  
S. Racca ◽  
G. Conti ◽  
M. Tampellini ◽  
F. Pietribiasi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis

scholarly journals Signatures of tumor–immune interactions as biomarkers for breast cancer prognosis

2012 ◽  
Vol 8 (6) ◽  
pp. 703-711 ◽  
Author(s):  
Masoud H Manjili ◽  
Kayvan Najarian ◽  
Xiang-Yang Wang
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis
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