scholarly journals 45P Analysis of HER2 distribution concordance in breast cancer tissue by serial IHC staining

2021 ◽  
Vol 32 ◽  
pp. S374
Author(s):  
G-R. Peng ◽  
C-H. Ye ◽  
J.Y.C. Lee ◽  
S. Hu ◽  
W-C. Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Tissue ◽  
Cancer Tissue

scholarly journals Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Siti Norbaini Sabtu ◽  
S. F. Abdul Sani ◽  
L. M. Looi ◽  
S. F. Chiew ◽  
Dharini Pathmanathan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Nucleic Acids ◽  
Raman Spectra ◽  
Cancer Progression ◽  
Component Analysis ◽  
Breast Cancer Tissue ◽  
Metabolic Changes ◽  
Cancer Tissue

AbstractThe epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600–1800 cm−1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey’s multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

Quantitative estimation of BRCA1 protein expression in breast cancer tissue using the method of flow cytometry

2016 ◽  
Vol 61 ◽  
pp. S183
Author(s):  
E. Shestakova ◽  
E. Dudko ◽  
A. Grishanina ◽  
V. Kirsanov ◽  
N. Vichljantzeva ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Flow Cytometry ◽  
Protein Expression ◽  
Quantitative Estimation ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Brca1 Protein

Detection of DNA fragmentation in human breast cancer tissue by an antibody specific to single-stranded DNA

Breast Cancer ◽  
1998 ◽  
Vol 5 (1) ◽  
pp. 47-52 ◽  
Author(s):  
Shunzo Kobayashi ◽  
Hirotaka Iwase ◽  
Yoshihiko Kawarada ◽  
Naoyuki Miura ◽  
Toshihiro Sugiyama ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Fragmentation ◽  
Human Breast Cancer ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Human Breast ◽  
Human Breast Cancer Tissue ◽  
Single Stranded Dna

Evaluation of photodynamic therapy efficiency using an in vitro three-dimensional microfluidic breast cancer tissue model

Lab on a Chip ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. 735-744 ◽  
Author(s):  
Yamin Yang ◽  
Xiaochuan Yang ◽  
Jin Zou ◽  
Chao Jia ◽  
Yue Hu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gold Nanoparticles ◽  
Photodynamic Therapy ◽  
Three Dimensional ◽  
Therapeutic Agents ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Tissue Model

A microfluidic-based in vitro three-dimensional (3D) breast cancer tissue model was established for determining the efficiency of photodynamic therapy (PDT) with therapeutic agents (photosensitizer and gold nanoparticles) under various irradiation conditions.

An inverse problem approach to stiffness mapping for early detection of breast cancer: tissue phantom experiments

2018 ◽  
Vol 27 (7) ◽  
pp. 1006-1037 ◽  
Author(s):  
Lorraine G. Olson ◽  
Robert D. Throne ◽  
Adam J. Nolte ◽  
Allison Crump ◽  
Kaelyn Griffin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Inverse Problem ◽  
Early Detection ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Tissue Phantom ◽  
Phantom Experiments

Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

2012 ◽  
Vol 11 (8) ◽  
pp. 4201-4210 ◽  
Author(s):  
Satoshi Muraoka ◽  
Hideaki Kume ◽  
Shio Watanabe ◽  
Jun Adachi ◽  
Masayoshi Kuwano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Tissue Samples
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