AIMC Topic: Lymphocytes, Tumor-Infiltrating
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Activated cancer-associated fibroblasts correlate with poor survival and decreased lymphocyte infiltration in infiltrative type distal cholangiocarcinoma.
Scientific reports
Jul 1, 2025
Cancer-associated fibroblasts promote tumor progression through growth facilitation, invasion, and immune evasion. This study investigated the impact of activated cancer-associated fibroblasts (aCAFs) on survival outcomes, immune response, and molecu...
Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer.
Frontiers in immunology
May 22, 2025
INTRODUCTION: Colorectal cancer (CRC), the third most common cancer worldwide, often shows limited responsiveness to immunotherapy due to its predominantly immune-excluded phenotype. Despite increasing insights into the complex tumor microenvironment...
Humans
Male
Gene Expression Profiling
Transcriptome
Cell Line, Tumor
Prognosis
Female
Colorectal Neoplasms
Tumor Microenvironment
Amino Acids
Single-Cell Analysis
Programmed Cell Death 1 Receptor
Gene Expression Regulation, Neoplastic
Tumor Escape
Lymphocytes, Tumor-Infiltrating
CD8-Positive T-Lymphocytes
Annotation-Free Whole-Slide Image Analysis Method to Assess Immune Infiltration in Colorectal Cancer.
JCO precision oncology
May 7, 2025
PURPOSE: Tumor-infiltrating lymphocytes (TILs) play a crucial role in host antitumor processes. High level of TILs is associated with better outcomes for patients. We aim to automatically quantify TILs without any nuclei annotation and further constr...
Constructing a neural network model based on tumor-infiltrating lymphocytes (TILs) to predict the survival of hepatocellular carcinoma patients.
PeerJ
Apr 23, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide, and early pathological diagnosis is crucial for formulating treatment plans. Despite the widespread attention to pathology in the treatment of HCC patients,...
An Ultrasound-based Machine Learning Model for Predicting Tumor-Infiltrating Lymphocytes in Breast Cancer.
Technology in cancer research & treatment
Apr 17, 2025
IntroductionTumor-infiltrating lymphocytes (TILs) are key indicators of immune response and prognosis in breast cancer (BC). Accurate prediction of TIL levels is essential for guiding personalized treatment strategies. This study aimed to develop and...
Pathogenomic fingerprinting to identify associations between tumor morphology and epigenetic states.
European journal of cancer (Oxford, England : 1990)
Apr 14, 2025
INTRODUCTION: Measuring the chromatin state of a tumor provides a powerful map of its epigenetic commitments; however, as these are generally bulk measurements, it has not yet been possible to connect changes in chromatin accessibility to the patholo...
A machine learning approach to risk-stratification of gastric cancer based on tumour-infiltrating immune cell profiles.
Annals of medicine
Apr 10, 2025
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease, and the response of patients to clinical treatment varies substantially. There is no satisfactory strategy for predicting curative effects to date. We aimed to explore a new method fo...
A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.
The Journal of pathology
Apr 3, 2025
Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichment of distinct T-cell subpopulations has been determined to impact the response to immune checkpoint ...
A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.
Frontiers in immunology
Mar 24, 2025
INTRODUCTION: Tumor-infiltrating B lymphocytes (TILBs) play a pivotal role in shaping the immune microenvironment of tumors (TIME) and in the progression of lung adenocarcinoma (LUAD). However, there remains a scarcity of research that has thoroughly...
Machine Learning and Mendelian Randomization Reveal a Tumor Immune Cell Profile for Predicting Bladder Cancer Risk and Immunotherapy Outcomes.
The American journal of pathology
Mar 21, 2025
This study's objective was to develop predictive models for bladder cancer (BLCA) using tumor infiltrated immune cell (TIIC)-related genes. Multiple RNA expression data and scRNA-seq were downloaded from the TCGA and GEO databases. A tissue specifici...
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