ArticleBJC reports2025
Deep-learning enabled combined measurement of tumour cell density and tumour infiltrating lymphocyte density as a prognostic biomarker in colorectal cancer.
Article in BJC reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Trial
- The density of tumour infiltrating lymphocytes in oesophago-gastric cancer varies with disease stage, geographical region and treatment: a post hoc analysis of nine phase III clinical trials.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Tumour-Stroma Ratio as a Predictive Biomarker for Neoadjuvant Therapy Efficacy in Rectal Cancer.Cancers · 2026Review
- Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation.BJC reports · 2026Review
- Integrating artificial intelligence (AI) into colorectal cancer reporting.The Journal of pathology · 2026Review
- TILseg: Automated Whole Slide-Level Spatial Scoring of Tumor-Infiltrating Lymphocytes Reveals Prognostic Patterns in Triple Negative Breast Cancer.medRxiv : the preprint server for health sciences · 2026Article
- Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.Journal of personalized medicine · 2026Review
- Article
- Immuno-Oncology at the Crossroads: Confronting Challenges in the Quest for Effective Cancer Therapies.International journal of molecular sciences · 2025Review
- Prognostic Impact of Klintrup-Mäkinen (KM) Score in Gastric Cancer and Its Association with Pathological Parameters.Medicina (Kaunas, Lithuania) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundWithin the colorectal cancer (CRC) tumour microenvironment, tumour infiltrating lymphocytes (TILs) and tumour cell density (TCD) are recognised prognostic markers. Measurement of TILs and TCD using deep-learning (DL) on haematoxylin and eosin (HE) whole slide images (WSIs) could aid management.
methodsHE WSIs from the primary tumours of 127 CRC patients were included. DL was used to quantify TILs across different regions of the tumour and TCD at the luminal surface. The relationship between TILs, TCD, and cancer-specific survival was analysed.
resultsMedian TIL density was higher at the invasive margin than the luminal surface (963 vs 795 TILs/mm
conclusionsDL derived TIL and TCD score were independently prognostic in CRC. Patients with low TILs and TCD are at the highest risk of cancer-specific death. DL quantification of TILs and TCD could be used in combination alongside other validated prognostic biomarkers in routine clinical practice.
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Registered trials
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