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Lymphocytes, Tumor-Infiltrating

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The global trends and distribution in tumor-infiltrating lymphocytes over the past 49 years: bibliometric and visualized analysis.

Frontiers in immunology
BACKGROUND: The body of research on tumor-infiltrating lymphocytes (TILs) is expanding rapidly; yet, a comprehensive analysis of related publications has been notably absent.

High density of TCF1+ stem-like tumor-infiltrating lymphocytes is associated with favorable disease-specific survival in NSCLC.

Frontiers in immunology
INTRODUCTION: Tumor-infiltrating lymphocytes are both prognostic and predictive biomarkers for immunotherapy response. However, less is known about the survival benefits oftheir subpopulations.

Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer.

The American journal of pathology
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...

Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.

Medical physics
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...

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

Scientific reports
The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma (LUAD) using machine learning (ML) techniques, focusing on early immune infiltration. Feature selection was performed on The Cancer Genome Atlas (TCGA...

Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer.

Biology direct
BACKGROUND: Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determining prognosis and response to immunotherapy in colorectal cancer (CRC) patients. While Whole Exome Sequencing (WES) stands as the gold standard for TMB...

Hepatocellular Carcinoma Immune Microenvironment Analysis: A Comprehensive Assessment with Computational and Classical Pathology.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: The spatial variability and clinical relevance of the tumor immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). In this study, we aim to develop a deep learning (DL)-based image analysis model for t...

Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer.

JAMA oncology
IMPORTANCE: Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to b...