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DOI 10.1080/14789450.2021.1984886

Медицинская библиотека · Expert review of proteomics · 2021

Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine.

Liotta Lance A, Pappalardo Philip A, Carpino Alan, Haymond Amanda, Howard Marissa, Espina Virginia, Wulfkuhle Julie, Petricoin Emanuel

СтатьяПоддержка NIH: внешняя программаПоддержка правительства СШАОбзорПеревод пока не подготовлен

Аннотация

INTRODUCTION

Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.

AREAS COVERED: We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.

EXPERT OPINION: LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.

Для цитирования: Liotta Lance A, Pappalardo Philip A, Carpino Alan, Haymond Amanda, Howard Marissa, Espina Virginia, Wulfkuhle Julie, Petricoin Emanuel. Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine.. Expert review of proteomics. 2021. DOI: 10.1080/14789450.2021.1984886.

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