Integrative Histopathological–Molecular–Computational Analysis of Primary Brain Tumors
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Informatics and Big Data".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 259
Special Issue Editor
Interests: brain tumor neuropathology; molecular pathology; bioinformatics and statistics; oncology; drug development and clinical trials
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The likelihood of developing a brain tumor during one’s lifespan is less than 1%; however, the burden of malignant disease has great impact on multiple domains: debilitating symptomatology, severe functional impairment, cognitive dysfunction, psychological trauma, familial and financial burden, and overall, on the absolute years of life lost. According to data from the Global Burden of Disease, the highest incidence and mortality for brain cancer were found in Europe and America, with Cuba leading in these statistics, while the lowest were observed in Africa. Primary brain cancers have increased in incidence worldwide, except in males from Southeast Asia. In the pediatric population, brain cancer represents the second-most common cancer after leukemias.
In the last 100 years, several technologies have contributed to brain tumor characterization. Optic microscopy initially helped describe tumor histomorphology and set the bases for tumor classification. Later, special tissue stains, immunohistochemistry, and electron microscopy helped refine the tumor morphology and provided more in-depth information about it. Recently, molecular techniques described several diagnostic, prognostic, and predictive biomarkers. Computer algorithms nuanced the interpretation of large molecular datasets and further expanded the wealth of information on these tumors.
The scope of this Special Issue is to bring histopathology into focus and encourage an integrative histopathological–molecular–computational analysis of primary brain tumors. Will the integrated data provide diagnostic, prognostic, or predictive information? Are there advantages to these types of integrations? Are there limitations in their application? How has digital pathology and artificial intelligence shaped the understanding of primary brain tumors? What computational modalities are the best for such analysis?
I am pleased to invite experts to share their innovative findings and opinions, hypothesize the novel models of disease, expand on current knowledge, and propose novel tumor classification schemes and computational modalities.
Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: histopathology and molecular correlations, computational pathology, pathological mechanisms, multi-omics, and targeted therapies.
I look forward to receiving your contributions.
Dr. Adriana Olar
Guest Editor
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Keywords
- brain tumor histopathology
- neuropathology
- molecular pathology
- digital pathology
- artificial intelligence
- bioinformatics
- computational pathology
- deep learning
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