Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction.
By Bernhard Mlecnik, M. Tosolini, A. Kirilovsky, A. Berger, Gabriela Bindea, T. Méatchi, P. Bruneval, Zlatko Trajanoski, W. Fridman, Franck Pagès and 1 more. Journal of Clinical Oncology, 2011
988 citations recorded by the source corpus.
Subfields: Oncology
View Paper: https://www.semanticscholar.org/paper/315226a53c448759a040db5631e9b33a6697c139
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Oncology
Citations in the corpus
- Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours (2013, background): “Given the major clinical importance of distinct tumour regions, it is appropriate to conduct immune cell infiltration evaluation systematically in the two separate areas, the core of the tumour and the invasive margin [9,10].”
- TIMER2.0 for analysis of tumor-infiltrating immune cells (2020, background): “Tumor-infiltrating T cells (26,27) and B cells (28,29) have been reported to affect patient clinical outcome.”
- Cancer classification using the Immunoscore: a worldwide task force (2012, methodology): “This was particularly illustrated in CRC [5,9,13,14,19], and should be applicable to most human tumors [23].”
- Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images (2018, positive): “At the same time, many observations suggest that high densities of tumor-infiltrating lymphocytes (TILs) correlate with favorable clinical outcomes (Mlecnik et al., 2011a) such as longer disease-free survival or improved overall survival (OS) in multiple cancer types (Angell and Galon, 2013).”
- Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade (2016, background): “, 2006) and showed that a prognostic marker termed immunoscore based on the quantification of these two subpopulations more accurately predicts survival than the standard TNM staging (Mlecnik et al., 2011).”
- AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020, positive): “The spatial distribution of lymphocytes with respect to tumor, tumor boundary and tumor associated stroma are also important factors in cancer prognosis [180].”