Automated Technology for Personalized Cancer Medicine: A Theme Issue in Honor of Prof. Dr. Thomas Grogan
A special issue of Hemato (ISSN 2673-6357).
Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 10349
Special Issue Editors
Interests: microscope-based techniques; immunohistochemistry; immunofluorescence; antibodies; biomarkers; hematological malignancies; solid tumors; immuno-oncopathology; tumor microenvironment; immunotherapy
Interests: immunohistochemistry; in situ molecular techniques; brightfield in situ hybridization; virologic characterization; EBV; HHV8/KSHV; HPV; tumor microenvironment; Hodgkin’s lymphoma; HIV-associated lymphomas
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Special Issue Information
Dear Colleagues,
This honorary issue celebrates Prof. Thomas Grogan, Emeritus Professor of Pathology at the University of Arizona and founder of Ventana Medical Systems Inc.
Prof Grogan’s scientific work was of great relevance in actively contributing to the development of the WHO classification of tumours of the hemopoietic and lymphoma tissues and his innovations in automated immunohistochemistry technology, as well as pre-analytical tissue processing, allowed him to develop several patents. The impact of these methodologies showed the clinical importance of cancer pathology, as they ensure reliable test results for determining patients’ treatment options. These advances, recognised by pathologists and clinical oncologists, further contributed to elevating the scientific importance of pathology.
We dedicate this honorary Special Issue to Prof. Tom Grogan, entitled "Automated Technology for Personalized Cancer Medicine", highlighting his major professional contributions, including novel development in the fields of immunohistology, in situ hybridization and clinical biomarkers.
The Special Issue will also focus on the impact of automated technologies on diagnostic and molecular pathology, as well as the identification of novel cancer therapies.
Prof. Dr. Teresa Marafioti
Prof. Dr. Annunziata Gloghini
Guest Editors
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Keywords
- personalized cancer medicine
- cancer diagnosis
- automated technology
- lymphoma classification
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