AIMC Topic: Lymphocytes, Tumor-Infiltrating
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Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.
Medical physics
Aug 17, 2024
BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable f...
Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer.
The American journal of pathology
Jul 19, 2024
Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of classification depended on the assessor's experience. This study aimed to deve...
Glycosylphosphatidylinositol anchor biosynthesis pathway-based biomarker identification with machine learning for prognosis and T cell exhaustion status prediction in breast cancer.
Frontiers in immunology
Jul 2, 2024
As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical...
Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.
Frontiers in immunology
Jun 28, 2024
INTRODUCTION: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified.
Machine learning evaluation of immune infiltrate through digital tumour score allows prediction of survival outcome in a pooled analysis of three international stage III colon cancer cohorts.
EBioMedicine
Jun 15, 2024
BACKGROUND: T-cell immune infiltrates are robust prognostic variables in localised colon cancer. Evaluation of prognosis using artificial intelligence is an emerging field. We evaluated whether machine learning analysis improved prediction of patient...
Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing.
British journal of cancer
Jun 7, 2024
BACKGROUND: It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for ident...
A Deep Learning-Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma.
The American journal of pathology
Mar 25, 2024
Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study develo...
A systematic review of machine learning-based tumor-infiltrating lymphocytes analysis in colorectal cancer: Overview of techniques, performance metrics, and clinical outcomes.
Computers in biology and medicine
Mar 13, 2024
The incidence of colorectal cancer (CRC), one of the deadliest cancers around the world, is increasing. Tissue microenvironment (TME) features such as tumor-infiltrating lymphocytes (TILs) can have a crucial impact on diagnosis or decision-making for...
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.
Breast cancer research : BCR
Nov 13, 2023
BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict t...
Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network.
The American journal of pathology
Sep 20, 2023
The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs o...
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