Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma
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Summary
The research demonstrates that computational pathology can be an efficient hypothesis generator for human pathology research, and support the histologic evaluation of SI as a prognostic biomarker in lung SCCs.
- Type
- article
- Published
- 2018-03-02
- Cited by
- 15
- References
- 42
- Access
- Open access
- OpenAlex
- https://openalex.org/W2789989802
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3625124
Keywords
Biomarker, Stromal cell, Medicine, Tissue microarray, Hazard ratio
References
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- International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma
- Concurrent infiltration by CD8+ T cells and CD4+ T cells is a favourable prognostic factor in non-small-cell lung carcinoma
- Prognostic Effect of Epithelial and Stromal Lymphocyte Infiltration in Non–Small Cell Lung Cancer
- Stromal Macrophage Expressing CD204 is Associated with Tumor Aggressiveness in Lung Adenocarcinoma
- Dendritic cells in tumor-associated tertiary lymphoid structures signal a Th1 cytotoxic immune contexture and license the positive prognostic value of infiltrating CD8+ T cells.
- The M1 form of tumor-associated macrophages in non-small cell lung cancer is positively associated with survival time
- Presence of B cells in tertiary lymphoid structures is associated with a protective immunity in patients with lung cancer.
- Nivolumab versus Docetaxel in Advanced Non-squamous Non-small Cell Lung Cancer
- Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma
- Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival
- The non-small cell lung cancer immune contexture. A major determinant of tumor characteristics and patient outcome.
- S 100 Positive Dendritic Cells In Human Lung Tumors Associated With Cell Differentiation And Enhanced Survival
- Pembrolizumab versus Ipilimumab in Advanced Melanoma.
Cited by
- Deep learning based on standard H&E images of primary melanoma tumors identifies patients at risk for visceral recurrence and death
- IASLC MULTIDISCIPLINARY RECOMMENDATIONS FOR PATHOLOGIC ASSESSMENT OF LUNG CANCER RESECTION SPECIMENS FOLLOWING NEOADJUVANT THERAPY
- New methodologies in ageing research.
- Machine learning-based histological classification that predicts recurrence of peripheral lung squamous cell carcinoma.
- Immunocytokines are a promising immunotherapeutic approach against glioblastoma
- Biopsy-free in vivo virtual histology of skin using deep learning
- Prognostic Value of Selected Histologic Features for Lung Squamous Cell Carcinoma
- The state of the art for artificial intelligence in lung digital pathology
- The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy
- An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics
- Prediction of Ovarian Cancer Response to Therapy Based on Deep Learning Analysis of Histopathology Images
- Comparative performance of PD‐L1 scoring by pathologists and AI algorithms
- Computational analysis of whole slide images predicts PD-L1 expression and progression-free survival in immunotherapy-treated non-small cell lung cancer patients
- Clinician Perspectives on Digital and Computational Pathology: Clinical Benefits, Concerns, and Willingness to Adopt
- An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics
- NLR inflammasome pathways: key targets for pathogenesis and therapy of metabolic diseases
- Application of artificial intelligence in lung cancer diagnosis, therapy, and prognosis
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