Analysis of histological sections of disease tissues has traditionally relied on pathologist-based scoring. In an Advanced Online Publication in Nature Medicine Camp et al. describe techniques to ...

To study tissue samples from multiple patients, researchers use tissue microarrays (TMAs), a technology in which hundreds of tissue cores are arranged on a single glass slide for analysis by ...

Abstract The use of tissue microarrays (TMAs) in the preclinical and translational research settings has become ubiquitous as they allow for high-throughput in situ biomarker analysis of hundreds ...

High-Throughput Tissue Microarray Analysis Used to Evaluate Biology and Prognostic Significance of the E-Cadherin Pathway in Non–Small-Cell Lung Cancer ...

Applying tissue microarray (TMA) analysis, we correlated HSP27 protein expression with clinical-pathological parameters in surgical specimen from 86 pancreatic cancer patients. Methods: ...

Additionally, tissue analysis methods that can be performed on whole tissue sections can be applied to TMAs, including immunohistochemistry (IHC), [16] immunofluorescence, [17, 18] FISH, [19 ...

One of the potential disadvantages of tissue microarray analysis is that a single small core may not accurately represent the entire tumor.

A single tissue can be transferred to up to ten membranes, each of which is probed with different antibodies, detected with fluorescent secondary antibodies, and quantified by a microarray scanner.

The method of choice used for preparing tissue samples can lead to biased results in the analysis of cancer patient survival.

Explore how new AI technology speeds up whole-slide cancer analysis for better research and treatment strategies. Keep reading.

Accurate classification of tissue samples is an essential tool in disease diagnosis and treatment. The DNA microarray technology enables disease classification based only on gene expression analysis, ...