scholarly journals Protein Extraction from Formalin-fixed, Paraffin-embedded Tissue Sections: Quality Evaluation by Mass Spectrometry

2006 ◽  
Vol 54 (6) ◽  
pp. 739-743 ◽  
Author(s):  
Shan-Rong Shi ◽  
Cheng Liu ◽  
Brian M. Balgley ◽  
Cheng Lee ◽  
Clive R. Taylor
2014 ◽  
Vol 9 (9) ◽  
pp. 2149-2156 ◽  
Author(s):  
Shadi Toghi Eshghi ◽  
Shuang Yang ◽  
Xiangchun Wang ◽  
Punit Shah ◽  
Xingde Li ◽  
...  

1998 ◽  
Vol 46 (3) ◽  
pp. 397-403 ◽  
Author(s):  
Kimimasa Ikeda ◽  
Takushi Monden ◽  
Toshiyuki Kanoh ◽  
Masaki Tsujie ◽  
Hikaru Izawa ◽  
...  

We describe and discuss a method of protein extraction for Western blot analysis from formalin-fixed, paraffin-embedded tissue sections. From 5-mm2 50-μm-thick tissue sections, an abundance of proteins could be extracted by incubating the sections in lysis buffer containing 2% sodium dodecyl sulfate (SDS) at 100C for 20 min followed by incubation at 60C for 2 hr. Extracts yielded discernible protein bands ranging from 10 kD to 120 kD as identified by SDS-polyacrylamide gel electrophoresis (PAGE). Western blot analysis successfully detected membrane-bound protein such as E-cadherin, cytosolic protein such as β-catenin, and nuclear proteins including proliferating cell nuclear antigen (PCNA), mutant-type p53, cyclin D1, cyclin E, and cyclin-dependent kinases (CDKs). With this technique, we could examine cyclin D1 and CDK2 expression in small adenomas compared with cancer tissues and normal mucosa. The simple method of protein extraction described here should make it possible to use large-scale archives of formalin-fixed, paraffin-embedded samples for Western blot analysis, and its application could lead to detailed analysis of protein expression. This new technique should yield valuable information for molecular biology.


2020 ◽  
Author(s):  
Uwe Möginger ◽  
Niels Marcussen ◽  
Ole N. Jensen

AbstractPathology differentiation of renal cancer types is challenging due to tissue similarities or overlapping histological features of various tumor (sub)types. As assessment is often manually conducted outcomes can be prone to human error and therefore require high-level expertise and experience. Mass spectrometry can provide detailed histo-molecular information on tissue and is becoming increasingly popular in clinical settings. Spatially resolving technologies such as mass spectrometry imaging and quantitative microproteomics profiling in combination with machine learning approaches provide promising tools for automated tumor classification of clinical tissue sections.In this proof of concept study we used MALDI-MS imaging (MSI) and rapid LC-MS/MS-based microproteomics technologies (15 min/sample) to analyze formalin-fixed paraffin embedded (FFPE) tissue sections and classify renal oncocytoma (RO, n=11), clear cell renal cell carcinoma (ccRCC, n=12) and chromophobe renal cell carcinoma (ChRCC, n=5). Both methods were able to distinguish ccRCC, RO and ChRCC in cross-validation experiments. MSI correctly classified 87% of the patients whereas the rapid LC-MS/MS-based microproteomics approach correctly classified 100% of the patients.This strategy involving MSI and rapid proteome profiling by LC-MS/MS reveals molecular features of tumor sections and enables cancer subtype classification. Mass spectrometry provides a promising complementary approach to current pathological technologies for precise digitized diagnosis of diseases.


2012 ◽  
Vol 10 (1) ◽  
pp. 19 ◽  
Author(s):  
Keiichi Hatakeyama ◽  
Kanako Wakabayashi-Nakao ◽  
Yutaka Aoki ◽  
Shun-ichiro Ogura ◽  
Ken Yamaguchi ◽  
...  

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